Patent Description:
Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, is neither expressly or impliedly admitted as prior art against the present disclosure.

There are several video data encoding and decoding systems which involve transforming video data into a frequency domain representation, quantising the frequency domain coefficients and then applying some form of entropy encoding to the quantised coefficients. This can achieve compression of the video data. A corresponding decoding or decompression technique is applied to recover a reconstructed version of the original video data.

Current video codecs (coder-decoders) such as those used in H. <NUM>/MPEG-<NUM> Advanced Video Coding (AVC) achieve data compression primarily by only encoding the differences between successive video frames. These codecs use a regular array of so-called macroblocks, each of which is used as a region of comparison with a corresponding macroblock in a previous video frame, and the image region within the macroblock is then encoded according to the degree of motion found between the corresponding current and previous macroblocks in the video sequence, or between neighbouring macroblocks within a single frame of the video sequence.

High Efficiency Video Coding (HEVC), also known as H. <NUM> or MPEG-H Part <NUM>, is a proposed successor to H. <NUM>/MPEG-<NUM> AVC. It is intended for HEVC to improve video quality and double the data compression ratio compared to H. <NUM>, and for it to be scalable from <NUM> × <NUM> to <NUM> × <NUM> pixels resolution, roughly equivalent to bit rates ranging from 128kbit/s to 800Mbit/s.

Previously proposed arrangements are disclosed by <CIT>; <CIT> (English language family member <CIT>); and <CIT>.

The present disclosure addresses or mitigates problems arising from this processing.

Referring now to the drawings, <FIG> are provided to give schematic illustrations of apparatus or systems making use of the compression and/or decompression apparatus to be described below in connection with embodiments of the present technology.

All of the data compression and/or decompression apparatus to be described below may be implemented in hardware, in software running on a general-purpose data processing apparatus such as a general-purpose computer, as programmable hardware such as an application specific integrated circuit (ASIC) or field programmable gate array (FPGA) or as combinations of these. In cases where the embodiments are implemented by software and/or firmware, it will be appreciated that such software and/or firmware, and non-transitory data storage media by which such software and/or firmware are stored or otherwise provided, are considered as embodiments of the present technology.

<FIG> schematically illustrates an audio/video data transmission and reception system using video data compression and decompression.

An input audio/video signal <NUM> is supplied to a video data compression apparatus <NUM> which compresses at least the video component of the audio/video signal <NUM> for transmission along a transmission route <NUM> such as a cable, an optical fibre, a wireless link or the like. The compressed signal is processed by a decompression apparatus <NUM> to provide an output audio/video signal <NUM>. For the return path, a compression apparatus <NUM> compresses an audio/video signal for transmission along the transmission route <NUM> to a decompression apparatus <NUM>.

The compression apparatus <NUM> and decompression apparatus <NUM> can therefore form one node of a transmission link. The decompression apparatus <NUM> and decompression apparatus <NUM> can form another node of the transmission link. Of course, in instances where the transmission link is uni-directional, only one of the nodes would require a compression apparatus and the other node would only require a decompression apparatus.

<FIG> schematically illustrates a video display system using video data decompression. In particular, a compressed audio/video signal <NUM> is processed by a decompression apparatus <NUM> to provide a decompressed signal which can be displayed on a display <NUM>. The decompression apparatus <NUM> could be implemented as an integral part of the display <NUM>, for example being provided within the same casing as the display device. Alternatively, the decompression apparatus <NUM> maybe provided as (for example) a so-called set top box (STB), noting that the expression "set-top" does not imply a requirement for the box to be sited in any particular orientation or position with respect to the display <NUM>; it is simply a term used in the art to indicate a device which is connectable to a display as a peripheral device.

<FIG> schematically illustrates an audio/video storage system using video data compression and decompression. An input audio/video signal <NUM> is supplied to a compression apparatus <NUM> which generates a compressed signal for storing by a store device <NUM> such as a magnetic disk device, an optical disk device, a magnetic tape device, a solid state storage device such as a semiconductor memory or other storage device. For replay, compressed data is read from the storage device <NUM> and passed to a decompression apparatus <NUM> for decompression to provide an output audio/video signal <NUM>.

It will be appreciated that the compressed or encoded signal, and a storage medium such as a machine-readable non-transitory storage medium, storing that signal, are considered as embodiments of the present technology.

<FIG> schematically illustrates a video camera using video data compression. In <FIG>, an image capture device <NUM>, such as a charge coupled device (CCD) image sensor and associated control and read-out electronics, generates a video signal which is passed to a compression apparatus <NUM>. A microphone (or plural microphones) <NUM> generates an audio signal to be passed to the compression apparatus <NUM>. The compression apparatus <NUM> generates a compressed audio/video signal <NUM> to be stored and/or transmitted (shown generically as a schematic stage <NUM>).

The techniques to be described below relate primarily to video data compression and decompression. It will be appreciated that many existing techniques may be used for audio data compression in conjunction with the video data compression techniques which will be described, to generate a compressed audio/video signal. Accordingly, a separate discussion of audio data compression will not be provided. It will also be appreciated that the data rate associated with video data, in particular broadcast quality video data, is generally very much higher than the data rate associated with audio data (whether compressed or uncompressed). It will therefore be appreciated that uncompressed audio data could accompany compressed video data to form a compressed audio/video signal. It will further be appreciated that although the present examples (shown in <FIG>) relate to audio/video data, the techniques to be described below can find use in a system which simply deals with (that is to say, compresses, decompresses, stores, displays and/or transmits) video data. That is to say, the embodiments can apply to video data compression without necessarily having any associated audio data handling at all.

<FIG> therefore provides an example of a video capture apparatus comprising an image sensor and an encoding apparatus of the type to be discussed below. <FIG> therefore provides an example of a decoding apparatus of the type to be discussed below and a display to which the decoded images are output.

A combination of <FIG> may provide a video capture apparatus comprising an image sensor <NUM> and encoding apparatus <NUM>, decoding apparatus <NUM> and a display <NUM> to which the decoded images are output.

<FIG> schematically illustrate storage media, which store (for example) the compressed data generated by the apparatus <NUM>, <NUM>, the compressed data input to the apparatus <NUM> or the storage media or stages <NUM>, <NUM>. <FIG> schematically illustrates a disc storage medium such as a magnetic or optical disc, and <FIG> schematically illustrates a solid state storage medium such as a flash memory. Note that <FIG> can also provide examples of non-transitory machine-readable storage media which store computer software which, when executed by a computer, causes the computer to carry out one or more of the methods to be discussed below.

Therefore, the above arrangements provide examples of video storage, capture, transmission or reception apparatuses embodying any of the present techniques.

<FIG> provides a schematic overview of a video data compression and decompression apparatus.

A controller <NUM> controls the overall operation of the apparatus and, in particular when referring to a compression mode, controls a trial encoding processes by acting as a selector to select various modes of operation such as block sizes and shapes, and whether the video data is to be encoded losslessly or otherwise. The controller is considered to part of the image encoder or image decoder (as the case may be). Successive images of an input video signal <NUM> are supplied to an adder <NUM> and to an image predictor <NUM>. The image predictor <NUM> will be described below in more detail with reference to <FIG>. The image encoder or decoder (as the case may be) plus the intra-image predictor of <FIG> may use features from the apparatus of <FIG>. This does not mean that the image encoder or decoder necessarily requires every feature of <FIG> however.

The adder <NUM> in fact performs a subtraction (negative addition) operation, in that it receives the input video signal <NUM> on a "+" input and the output of the image predictor <NUM> on a "-" input, so that the predicted image is subtracted from the input image. The result is to generate a so-called residual image signal <NUM> representing the difference between the actual and projected images.

One reason why a residual image signal is generated is as follows. The data coding techniques to be described, that is to say the techniques which will be applied to the residual image signal, tend to work more efficiently when there is less "energy" in the image to be encoded. Here, the term "efficiently" refers to the generation of a small amount of encoded data; for a particular image quality level, it is desirable (and considered "efficient") to generate as little data as is practicably possible. The reference to "energy" in the residual image relates to the amount of information contained in the residual image. If the predicted image were to be identical to the real image, the difference between the two (that is to say, the residual image) would contain zero information (zero energy) and would be very easy to encode into a small amount of encoded data. In general, if the prediction process can be made to work reasonably well such that the predicted image content is similar to the image content to be encoded, the expectation is that the residual image data will contain less information (less energy) than the input image and so will be easier to encode into a small amount of encoded data.

The remainder of the apparatus acting as an encoder (to encode the residual or difference image) will now be described. The residual image data <NUM> is supplied to a transform unit or circuitry <NUM> which generates a discrete cosine transform (DCT) representation of blocks or regions of the residual image data. The DCT technique itself is well known and will not be described in detail here. Note also that the use of DCT is only illustrative of one example arrangement. Other transforms which might be used include, for example, the discrete sine transform (DST). A transform could also comprise a sequence or cascade of individual transforms, such as an arrangement in which one transform is followed (whether directly or not) by another transform. The choice of transform may be determined explicitly and/or be dependent upon side information used to configure the encoder and decoder.

The output of the transform unit <NUM>, which is to say, a set of DCT coefficients for each transformed block of image data, is supplied to a quantiser <NUM>. Various quantisation techniques are known in the field of video data compression, ranging from a simple multiplication by a quantisation scaling factor through to the application of complicated lookup tables under the control of a quantisation parameter. The general aim is twofold. Firstly, the quantisation process reduces the number of possible values of the transformed data. Secondly, the quantisation process can increase the likelihood that values of the transformed data are zero. Both of these can make the entropy encoding process, to be described below, work more efficiently in generating small amounts of compressed video data.

A data scanning process is applied by a scan unit <NUM>. The purpose of the scanning process is to reorder the quantised transformed data so as to gather as many as possible of the non-zero quantised transformed coefficients together, and of course therefore to gather as many as possible of the zero-valued coefficients together. These features can allow so-called run-length coding or similar techniques to be applied efficiently. So, the scanning process involves selecting coefficients from the quantised transformed data, and in particular from a block of coefficients corresponding to a block of image data which has been transformed and quantised, according to a "scanning order" so that (a) all of the coefficients are selected once as part of the scan, and (b) the scan tends to provide the desired reordering. One example scanning order which can tend to give useful results is a so-called up-right diagonal scanning order.

The scanned coefficients are then passed to an entropy encoder (EE) <NUM>. Again, various types of entropy encoding may be used. Two examples are variants of the so-called CABAC (Context Adaptive Binary Arithmetic Coding) system and variants of the so-called CAVLC (Context Adaptive Variable-Length Coding) system. In general terms, CABAC is considered to provide a better efficiency, and in some studies has been shown to provide a <NUM>-<NUM>% reduction in the quantity of encoded output data for a comparable image quality compared to CAVLC. However, CAVLC is considered to represent a much lower level of complexity (in terms of its implementation) than CABAC. Note that the scanning process and the entropy encoding process are shown as separate processes, but in fact can be combined or treated together. That is to say, the reading of data into the entropy encoder can take place in the scan order. Corresponding considerations apply to the respective inverse processes to be described below.

The output of the entropy encoder <NUM>, along with additional data (mentioned above and/or discussed below), for example defining the manner in which the predictor <NUM> generated the predicted image, provides a compressed output video signal <NUM>.

However, a return path is also provided because the operation of the predictor <NUM> itself depends upon a decompressed version of the compressed output data.

The reason for this feature is as follows. At the appropriate stage in the decompression process (to be described below) a decompressed version of the residual data is generated. This decompressed residual data has to be added to a predicted image to generate an output image (because the original residual data was the difference between the input image and a predicted image). In order that this process is comparable, as between the compression side and the decompression side, the predicted images generated by the predictor <NUM> should be the same during the compression process and during the decompression process. Of course, at decompression, the apparatus does not have access to the original input images, but only to the decompressed images. Therefore, at compression, the predictor <NUM> bases its prediction (at least, for inter-image encoding) on decompressed versions of the compressed images.

The entropy encoding process carried out by the entropy encoder <NUM> is considered (in at least some examples) to be "lossless", which is to say that it can be reversed to arrive at exactly the same data which was first supplied to the entropy encoder <NUM>. So, in such examples the return path can be implemented before the entropy encoding stage. Indeed, the scanning process carried out by the scan unit <NUM> is also considered lossless, but in the present embodiment the return path <NUM> is from the output of the quantiser <NUM> to the input of a complimentary inverse quantiser <NUM>. In instances where loss or potential loss is introduced by a stage, that stage may be included in the feedback loop formed by the return path. For example, the entropy encoding stage can at least in principle be made lossy, for example by techniques in which bits are encoded within parity information. In such an instance, the entropy encoding and decoding should form part of the feedback loop.

In general terms, an entropy decoder <NUM>, the reverse scan unit <NUM>, an inverse quantiser <NUM> and an inverse transform unit or circuitry <NUM> provide the respective inverse functions of the entropy encoder <NUM>, the scan unit <NUM>, the quantiser <NUM> and the transform unit <NUM>. For now, the discussion will continue through the compression process; the process to decompress an input compressed video signal will be discussed separately below.

In the compression process, the scanned coefficients are passed by the return path <NUM> from the quantiser <NUM> to the inverse quantiser <NUM> which carries out the inverse operation of the scan unit <NUM>. An inverse quantisation and inverse transformation process are carried out by the units <NUM>, <NUM> to generate a compressed-decompressed residual image signal <NUM>.

The image signal <NUM> is added, at an adder <NUM>, to the output of the predictor <NUM> to generate a reconstructed output image <NUM>. This forms one input to the image predictor <NUM>, as will be described below.

Turning now to the process applied to decompress a received compressed video signal <NUM>, the signal is supplied to the entropy decoder <NUM> and from there to the chain of the reverse scan unit <NUM>, the inverse quantiser <NUM> and the inverse transform unit <NUM> before being added to the output of the image predictor <NUM> by the adder <NUM>. So, at the decoder side, the decoder reconstructs a version of the residual image and then applies this (by the adder <NUM>) to the predicted version of the image (on a block by block basis) so as to decode each block. In straightforward terms, the output <NUM> of the adder <NUM> forms the output decompressed video signal <NUM>. In practice, further filtering may optionally be applied (for example, by a filter <NUM> shown in <FIG> but omitted from <FIG> for clarity of the higher level diagram of <FIG>) before the signal is output.

The apparatus of <FIG> and <FIG> can act as a compression (encoding) apparatus or a decompression (decoding) apparatus. The functions of the two types of apparatus substantially overlap. The scan unit <NUM> and entropy encoder <NUM> are not used in a decompression mode, and the operation of the predictor <NUM> (which will be described in detail below) and other units follow mode and parameter information contained in the received compressed bit-stream rather than generating such information themselves.

<FIG> schematically illustrates the generation of predicted images, and in particular the operation of the image predictor <NUM>.

There are two basic modes of prediction carried out by the image predictor <NUM>: so-called intra-image prediction and so-called inter-image, or motion-compensated (MC), prediction. At the encoder side, each involves detecting a prediction direction in respect of a current block to be predicted, and generating a predicted block of samples according to other samples (in the same (intra) or another (inter) image). By virtue of the units <NUM> or <NUM>, the difference between the predicted block and the actual block is encoded or applied so as to encode or decode the block respectively.

(At the decoder, or at the reverse decoding side of the encoder, the detection of a prediction direction may be in response to data associated with the encoded data by the encoder, indicating which direction was used at the encoder. Or the detection may be in response to the same factors as those on which the decision was made at the encoder).

Intra-image prediction bases a prediction of the content of a block or region of the image on data from within the same image. This corresponds to so-called I-frame encoding in other video compression techniques. In contrast to I-frame encoding, however, which involves encoding the whole image by intra-encoding, in the present embodiments the choice between intra- and inter- encoding can be made on a block-by-block basis, though in other embodiments the choice is still made on an image-by-image basis.

Motion-compensated prediction is an example of inter-image prediction and makes use of motion information which attempts to define the source, in another adjacent or nearby image, of image detail to be encoded in the current image. Accordingly, in an ideal example, the contents of a block of image data in the predicted image can be encoded very simply as a reference (a motion vector) pointing to a corresponding block at the same or a slightly different position in an adjacent image.

A technique known as "block copy" prediction is in some respects a hybrid of the two, as it uses a vector to indicate a block of samples at a position displaced from the currently predicted block within the same image, which should be copied to form the currently predicted block.

Returning to <FIG>, two image prediction arrangements (corresponding to intra- and inter-image prediction) are shown, the results of which are selected by a multiplexer <NUM> under the control of a mode signal <NUM> (for example, from the controller <NUM>) so as to provide blocks of the predicted image for supply to the adders <NUM> and <NUM>. The choice is made in dependence upon which selection gives the lowest "energy" (which, as discussed above, may be considered as information content requiring encoding), and the choice is signalled to the decoder within the encoded output data-stream. Image energy, in this context, can be detected, for example, by carrying out a trial subtraction of an area of the two versions of the predicted image from the input image, squaring each pixel value of the difference image, summing the squared values, and identifying which of the two versions gives rise to the lower mean squared value of the difference image relating to that image area. In other examples, a trial encoding can be carried out for each selection or potential selection, with a choice then being made according to the cost of each potential selection in terms of one or both of the number of bits required for encoding and distortion to the picture.

The actual prediction, in the intra-encoding system, is made on the basis of image blocks received as part of the signal <NUM>, which is to say, the prediction is based upon encodeddecoded image blocks in order that exactly the same prediction can be made at a decompression apparatus. However, data can be derived from the input video signal <NUM> by an intra-mode selector <NUM> to control the operation of the intra-image predictor <NUM>.

For inter-image prediction, a motion compensated (MC) predictor <NUM> uses motion information such as motion vectors derived by a motion estimator <NUM> from the input video signal <NUM>. Those motion vectors are applied to a processed version of the reconstructed image <NUM> by the motion compensated predictor <NUM> to generate blocks of the inter-image prediction.

Accordingly, the units <NUM> and <NUM> (operating with the estimator <NUM>) each act as detectors to detect a prediction direction in respect of a current block to be predicted, and as a generator to generate a predicted block of samples (forming part of the prediction passed to the units <NUM> and <NUM>) according to other samples defined by the prediction direction.

The processing applied to the signal <NUM> will now be described. Firstly, the signal is optionally filtered by a filter unit <NUM>, which will be described in greater detail below. This involves applying a "deblocking" filter to remove or at least tend to reduce the effects of the block-based processing carried out by the transform unit <NUM> and subsequent operations. A sample adaptive offsetting (SAO) filter may also be used. Also, an adaptive loop filter is optionally applied using coefficients derived by processing the reconstructed signal <NUM> and the input video signal <NUM>. The adaptive loop filter is a type of filter which, using known techniques, applies adaptive filter coefficients to the data to be filtered. That is to say, the filter coefficients can vary in dependence upon various factors. Data defining which filter coefficients to use is included as part of the encoded output data-stream.

The filtered output from the filter unit <NUM> in fact forms the output video signal <NUM> when the apparatus is operating as a decompression apparatus. It is also buffered in one or more image or frame stores <NUM>; the storage of successive images is a requirement of motion compensated prediction processing, and in particular the generation of motion vectors. To save on storage requirements, the stored images in the image stores <NUM> may be held in a compressed form and then decompressed for use in generating motion vectors. For this particular purpose, any known compression / decompression system may be used. The stored images are passed to an interpolation filter <NUM> which generates a higher resolution version of the stored images; in this example, intermediate samples (sub-samples) are generated such that the resolution of the interpolated image is output by the interpolation filter <NUM> is <NUM> times (in each dimension) that of the images stored in the image stores <NUM> for the luminance channel of <NUM>:<NUM>:<NUM> and <NUM> times (in each dimension) that of the images stored in the image stores <NUM> for the chrominance channels of <NUM>:<NUM>:<NUM>. The interpolated images are passed as an input to the motion estimator <NUM> and also to the motion compensated predictor <NUM>.

The way in which an image is partitioned for compression processing will now be described. At a basic level, an image to be compressed is considered as an array of blocks or regions of samples. The splitting of an image into such blocks or regions can be carried out by a decision tree, such as that described in <NPL>. In some examples, the resulting blocks or regions have sizes and, in some cases, shapes which, by virtue of the decision tree, can generally follow the disposition of image features within the image. This in itself can allow for an improved encoding efficiency because samples representing or following similar image features would tend to be grouped together by such an arrangement. In some examples, square blocks or regions of different sizes (such as 4x4 samples up to, say, 64x64 or larger blocks) are unavailable for selection. In other example arrangements, blocks or regions of different shapes such as rectangular blocks (for example, vertically or horizontally oriented) can be used. Other non-square and non-rectangular blocks are envisaged. The result of the division of the image into such blocks or regions is (in at least the present examples) that each sample of an image is allocated to one, and only one, such block or region.

The intra-prediction process will now be discussed. In general terms, intra-prediction involves generating a prediction of a current block of samples from previously-encoded and decoded samples in the same image.

<FIG> schematically illustrates a partially encoded image <NUM>. Here, the image is being encoded from top-left to bottom-right on a block by block basis. An example block encoded partway through the handling of the whole image is shown as a block <NUM>. A shaded region <NUM> above and to the left of the block <NUM> has already been encoded. The intra-image prediction of the contents of the block <NUM> can make use of any of the shaded area <NUM> but cannot make use of the unshaded area below that.

In some examples, the image is encoded on a block by block basis such that larger blocks (referred to as coding units or CUs) are encoded in an order such as the order discussed with reference to <FIG>. Within each CU, there is the potential (depending on the block splitting process that has taken place) for the CU to be handled as a set of two or more smaller blocks or transform units (TUs). This can give a hierarchical order of encoding so that the image is encoded on a CU by CU basis, and each CU is potentially encoded on a TU by TU basis. Note however that for an individual TU within the current coding tree unit (the largest node in the tree structure of block division), the hierarchical order of encoding (CU by CU then TU by TU) discussed above means that there may be previously encoded samples in the current CU and available to the coding of that TU which are, for example, above-right or belowleft of that TU.

The block <NUM> represents a CU; as discussed above, for the purposes of intra-image prediction processing, this may be subdivided into a set of smaller units. An example of a current TU <NUM> is shown within the CU <NUM>. More generally, the picture is split into regions or groups of samples to allow efficient coding of signalling information and transformed data. The signalling of the information may require a different tree structure of sub-divisions to that of the transform, and indeed that of the prediction information or the prediction itself. For this reason, the coding units may have a different tree structure to that of the transform blocks or regions, the prediction blocks or regions and the prediction information. In some examples such as HEVC the structure can be a so-called quad tree of coding units, whose leaf nodes contain one or more prediction units and one or more transform units; the transform units can contain multiple transform blocks corresponding to luma and chroma representations of the picture, and prediction could be considered to be applicable at the transform block level. In examples, the parameters applied to a particular group of samples can be considered to be predominantly defined at a block level, which is potentially not of the same granularity as the transform structure.

The intra-image prediction takes into account samples coded prior to the current TU being considered, such as those above and/or to the left of the current TU. Source samples, from which the required samples are predicted, may be located at different positions or directions relative to the current TU. To decide which direction is appropriate for a current prediction unit, the mode selector <NUM> of an example encoder may test all combinations of available TU structures for each candidate direction and select the prediction direction and TU structure with the best compression efficiency.

The picture may also be encoded on a "slice" basis. In one example, a slice is a horizontally adjacent group of CUs. But in more general terms, the entire residual image could form a slice, or a slice could be a single CU, or a slice could be a row of CUs, and so on. Slices can give some resilience to errors as they are encoded as independent units. The encoder and decoder states are completely reset at a slice boundary. For example, intra-prediction is not carried out across slice boundaries; slice boundaries are treated as image boundaries for this purpose.

<FIG> schematically illustrates a set of possible (candidate) prediction directions. The full set of candidate directions is available to a prediction unit. The directions are determined by horizontal and vertical displacement relative to a current block position, but are encoded as prediction "modes", a set of which is shown in <FIG>. Note that the so-called DC mode represents a simple arithmetic mean of the surrounding upper and left-hand samples. Note also that the set of directions shown in <FIG> is just one example; in other examples, a set of (for example) <NUM> angular modes plus DC and planar (a full set of <NUM> modes) as shown schematically in <FIG> makes up the full set. Other numbers of modes could be used.

In general terms, after detecting a prediction direction, the systems are operable to generate a predicted block of samples according to other samples defined by the prediction direction. In examples, the image encoder is configured to encode data identifying the prediction direction selected for each sample or region of the image (and the image decoder is configured to detect such data).

<FIG> schematically illustrates an intra-prediction process in which a sample <NUM> of a block or region <NUM> of samples is derived from other reference samples <NUM> of the same image according to a direction <NUM> defined by the intra-prediction mode associated with that sample. The reference samples <NUM> in this example come from blocks above and to the left of the block <NUM> in question and the predicted value of the sample <NUM> is obtained by tracking along the direction <NUM> to the reference samples <NUM>. The direction <NUM> might point to a single individual reference sample but in a more general case an interpolated value between surrounding reference samples is used as the prediction value. Note that the block <NUM> could be square as shown in <FIG> or could be another shape such as rectangular.

<FIG> schematically illustrate a previously proposed reference sample projection process.

In <FIG>, a block or region <NUM> of samples to be predicted is surrounded by linear arrays of reference samples from which the intra prediction of the predicted samples takes place. The reference samples <NUM> are shown as shaded blocks in <FIG>, and the samples to be predicted are shown as unshaded blocks. Note that an 8x8 block or region of samples to be predicted is used in this example, but the techniques are applicable to variable block sizes and indeed block shapes.

As mentioned, the reference samples comprise at least two linear arrays in respective orientations with respect to the current image region of samples to be predicted. For example, the linear arrays may be an array or row <NUM> of samples above the block of samples to be predicted and an array or column <NUM> of samples to the left of the block of samples to be predicted.

As discussed above with reference to <FIG>, the reference sample arrays can extend beyond the extent of the block to be predicted, in order to provide for prediction modes or directions within the range indicated in <FIG>. Where necessary, if previously decoded samples are not available for use as reference samples at particular reference sample positions, other reference samples can be re-used at those missing positions. Reference sample filtering processes can be used on the reference samples.

A sample projection process is used to project at least some of the reference samples to different respective positions with respect to the current image region, in the manner shown in <FIG>. In other words, in embodiments, the projection process and circuitry operates to represent at least some of the reference samples at different spatial positions relative to the current image region, for example as shown in <FIG>. Thus at least some reference samples may be moved (for the purposes at least of defining an array of reference samples from which samples are predicted) with respect to their relative positions to the current image region. In particular, <FIG> relates to a projection process performed for modes which are generally to the left of the diagonal mode (<NUM> in <FIG>) mainly modes <NUM>. <NUM>, and <FIG> schematically illustrates a reference sample projection carried for modes <NUM>. <NUM>, namely those generally above the block to be predicted (to the right of the diagonal mode <NUM>). The diagonal mode <NUM> can be assigned to either of these two groups as an arbitrary selection, such as to the group of modes to the right of the diagonal. So, in <FIG>, when the current prediction mode is between modes <NUM> and <NUM> (or their equivalent in a system such as that of <FIG> having a different number of possible prediction modes), the sample array <NUM> above the current block is projected to form additional reference samples <NUM> in the left hand column. Prediction then takes place with respect to the linear projected array <NUM> formed of the original left hand column <NUM> and the projected samples <NUM>. In <FIG>, for modes between <NUM> and <NUM> of <FIG> (or their equivalent in other sets of prediction modes such as those shown in <FIG>), the reference samples <NUM> in the left hand column are projected so as to extend to the left of the reference samples <NUM> above the current block. This forms a projected array <NUM>.

One reason why projection of this nature is carried out is to reduce the complexity of the intra prediction process, in that all of the samples to be predicted are then referencing a single linear array of reference samples, rather than referencing two orthogonal linear arrays.

<FIG> schematically illustrates a previously proposed prediction circuitry <NUM> arranged to carry out the projection process of <FIG>, specifically by providing projection circuitry <NUM> configured to carry out a projection process on the reference samples currently selected for a block of region to be predicted. The projected reference samples are stored in a buffer <NUM> to be accessed by an intra predictor <NUM> to generate predicted samples from the projected reference samples. The projection process is carried out according to the prediction mode associated with the current block to be predicted, using the techniques discussed in connection with <FIG>.

In embodiments, the same projection process is carried out in the decoder and in the encoder, so that the predicted samples are the same in each instance. Possible variations in operation between the use of prediction modes which will be referred to as "straight modes" and prediction modes which will be referred to as "curved modes" will now be discussed.

As further background, <FIG> schematically illustrate an example technique by which samples <NUM> of a current region <NUM> or block to be predicted, are predicted from reference samples <NUM>. In this example, the reference samples have been projected into a linear array using the techniques described with reference to <FIG> above.

A system of (x, y) coordinates is used for convenience, to allow individual reference or predicted sample positions to be identified. In the example of <FIG>, x coordinates are shown by a row <NUM> of numbers, and y coordinates are shown by a column <NUM> of numbers. So, each reference or predicted sample position has an associated (x, y) designation using the coordinate system.

In the example of <FIG>, a generally vertical mode (for example, a mode which is more vertical than horizontal) <NUM>, such as mode <NUM> in the designation of <FIG>, noting that a different mode number could be used if the set of modes shown in <FIG> were employed, has been selected for prediction of samples <NUM> of the block or region <NUM>. As discussed above with reference to <FIG>, such a generally vertical prediction mode is handled by the circuitry of <FIG> by projecting the left column of reference samples into an extension <NUM> of the reference samples above the block or region <NUM>.

Each of the samples to be predicted <NUM> is predicted as follows. For each sample to be predicted, there is an associated (x, y) location such as a location (<NUM>, <NUM>) for a sample <NUM> or a location (<NUM>, <NUM>) for a sample <NUM>. These two samples are used purely by way of example and the same technique applies to each of the samples <NUM> to be predicted.

The sample positions of the samples <NUM>, <NUM> to be predicted are mapped according to the direction <NUM> associated with the current prediction mode to respective locations or reference positions <NUM>, <NUM> among the reference samples. This mapping may be carried out using an expression such as that shown below, noting that this is a linear expression with respect to the coordinate system (x, y):.

and where i(p)=floor(p), is the value p rounded down (towards negative infinity) to the nearest integer, f(p)=p-i(p) represents the fractional part of the value p.

A is an angle parameter indicating the angle of the current mode. To illustrate, for example, for a horizontal or vertical line, A would be <NUM>; for a <NUM>° diagonal line, A would be ±<NUM>.

Those skilled in the art would appreciate that integer approximations can be used to simplify the linear equations, for example, representing the angle parameter A as a fractional fixed-precision number. In HEVC, the angles have an accuracy of <NUM> fractional bits.

So, for example, each sample to be predicted is associated with a coordinate position within the current region; and the intra-image predictor is configured to detect the reference position for a given sample to be predicted as a function of the coordinate position of the given sample to be predicted, the function depending upon the selected prediction mode.

In example arrangements, the reference position <NUM>, <NUM> is detected to an accuracy or resolution of less than one sample, which is to say with reference to the reference sample locations (-<NUM>, -<NUM>). (<NUM>, -<NUM>), a fractional value is used for the x coordinate of the reference position within the projected set of reference samples <NUM>. For example, the reference position could be detected to a resolution of <NUM>/<NUM> of a sample separation, so that the x coordinate of the reference positions <NUM>, <NUM> is identified to that resolution. The y coordinate of the reference position is -<NUM> in each case, but this is in fact irrelevant to the calculations that then take place, which relate to interpolation along the x axis of the reference samples <NUM>.

The prediction of the predicted values <NUM>, <NUM> is an interpolation of the value applicable to the detected x coordinate of the reference sample position <NUM>, <NUM>, for example as described above in the formulae shown earlier.

A similar arrangement is shown schematically in <FIG>, except that a generally horizontal prediction mode, for example a prediction mode which is more horizontal than vertical, such as (for example) mode <NUM> of the set shown in <FIG> (or a corresponding number for a similar mode in the set shown in <FIG>) having a prediction direction <NUM> is used. The selection of the particular prediction mode applies to the whole of the block or region <NUM> of samples <NUM> to be predicted and the particular example here is chosen purely for the purposes of the present explanation.

In the case of a generally horizontal mode, as discussed above, the projection circuitry shown in <FIG> projects those reference samples from above the block or region <NUM> to form an extension <NUM> of reference samples to the left of the region. Once again, the derivation of two example samples to be predicted, samples <NUM>, <NUM>, is shown, such that the sample position <NUM>, <NUM> are mapped using the direction <NUM> into reference positions <NUM>, <NUM> amongst the set of reference samples <NUM>. Once again, a similar (x, y) coordinate system is used and the reference positions <NUM>, <NUM> are expressed to a <NUM>/<NUM> sample resolution in the y-direction. The x coordinate of the reference sample positions is -<NUM> but this is irrelevant to the process which follows. The sample values of the samples to be predicted are obtained in the manner described above.

In these arrangements, the intra predictor <NUM> provides an example of a detector configured to detect the reference position as an array position, with respect to an array of the reference samples, pointed to by the prediction direction applicable to the current sample to be predicted; and a filter configured to generate the predicted sample by interpolation of the array of reference samples at the detected array position. The detector may be configured to detect the array position to an accuracy of less than one sample such as <NUM>/<NUM> sample.

The intra mode selector <NUM> the selector may be configured to perform at least a partial encoding to select the prediction mode.

<FIG> schematically illustrates a prediction process.

In the arrangements of <FIG>, for example, the reference samples <NUM>, <NUM> comprised a single row and column of samples around the current region or block to be predicted. In <FIG>, this single row and single column were projected to form either an elongate single row in <FIG> or an elongate single column in <FIG>. But the origin of the reference sample in both cases was a single row and column to the left of and above the current region.

Further possibilities will now be discussed in which, in at least some example circumstances, multiple rows and/or multiple columns of reference samples are used.

<FIG> schematically illustrates a situation relating to an 8x8 block <NUM> of reference samples <NUM>. The example used here is of an 8x8 block, but it will be appreciated that the present techniques can apply to various sizes and indeed shapes of blocks. So, the present techniques could apply to other sizes such as 4x4, 16x16, 32x32, 64x64 blocks or the like, or to non-square blocks such as (purely by way of example) 8x16 or the like. So, references to the 8x8 blocks are purely for the purposes of illustrative discussion.

In <FIG>, two rows of reference samples are used above the block or region <NUM> and two columns of reference samples are used to the left of the block or region <NUM>. Purely by way of example, a prediction direction <NUM> is assumed to have been selected for the block <NUM>. This could correspond, for example, to the mode <NUM> in the notation of <FIG> or a corresponding mode in the notation of <FIG>. The interpolation or prediction of a particular example predicted sample <NUM> will be discussed, but similar techniques apply to each of the samples <NUM> to be predicted in the block or region <NUM>.

Discussing first the reference samples, it will be seen that the reference samples in use in <FIG> comprise a row and column <NUM> spatially nearest to the block <NUM>, along with a further row or column <NUM> next-adjacent to the row and column <NUM>. It can also be seen that the row and column <NUM> extends further (to reference samples <NUM>, <NUM>) than the row and column <NUM>, in order to allow for prediction over the range of angles corresponding to the prediction modes <NUM>. <NUM> in <FIG> or the equivalent in <FIG> to be used. The reference samples <NUM>, <NUM> can simply be drawn from previously decoded reference samples in the normal way. If they are unavailable (because they have not yet been decoded) then next-adjacent samples <NUM>, <NUM> can be repeated to form the samples <NUM>, <NUM> respectively, or alternatively an extrapolation process can be used as discussed below.

Turning to the interpolation of the sample <NUM>, it can be seen that applying the direction <NUM> defined by the current prediction mode points to a reference position <NUM> in the first row and column <NUM> of reference samples. Extending the prediction direction points to a further position <NUM> in the second row and column <NUM>. The reference samples around these two reference positions have been annotated as reference samples a. g for clarity of the following explanation. It is also assumed, by way of example, that a <NUM>-tap interpolation process such as the process discussed above is used to derive a predicted sample. Of course, other interpolation techniques could be used and the following discussion would simply be adapted accordingly.

<FIG> relate to various possible techniques which can be applied by the intra predictor <NUM> for making use of two rows and columns of reference samples in the form shown in <FIG>.

Considering first, <FIG>, the reference position <NUM> is taken into account and the three samples in the row and column <NUM> (namely the reference samples b, d, f) and the reference samples in the row and column <NUM> (namely the reference samples c, e, g), which is to say the reference samples within a range <NUM> pointed to by the prediction direction in use, are combined. So in this example, pairs of reference samples, one from each of the rows/columns <NUM>, <NUM>, are combined in respective groups and the resulting combined reference samples are then used in an interpolation process. The selection of the reference samples to be combined is based upon the reference position <NUM> in the row/column <NUM> and separately on the reference position <NUM> in the row/column <NUM>. This means that a range <NUM> of reference samples in the row/column <NUM> is used, and (according to the prediction direction in use) a different - or at least potentially different - range <NUM> of reference samples (c, e, g) is used in dependence upon the reference position <NUM> in the row/column <NUM>. The combination takes place between the pairs of reference samples, which is to say that reference samples c and b are combined to form a reference sample h; reference samples e and d are combined to form a reference sample i; and reference samples g and f are combined to form a reference sample j. The reference sample h, i and j are then processed by (in this example) a three-tap interpolation process to form a predicted sample p.

The combination applied to the pairs of reference samples (c, b), (e, d), (g, f) is shown by an arbitrary symbol "Θ" to indicate that various possibilities exist for the nature of this combination. This combination could be a simple arithmetic mean. In other examples, it could be a weighted mean, for example so as to apply a greater weight to the reference samples (b, d, f in this example) spatially closer to the block <NUM> than the reference samples (c, e, g) spatially further away from the block <NUM>. For example, in the situation of <FIG> in which two rows and columns of reference samples are used, the weighting could be <NUM> for the closer reference samples and <NUM> for the further-away sample in each pair, so that (for example) h = <NUM>. 4c + <NUM>. In a situation such as one to be discussed below in which (for example) three or four rows and columns of reference samples are used, a weighting could be applied in a similar manner as follows (where Rn is a reference sample in row/column n, where n=<NUM> for the row/column spatially closest to the block or region to be predicted):.

Of course, other combinations, or indeed equal combinations, could be used.

So, in the example above. , a combination process such as an arithmetic mean or a weighted arithmetic mean is used to combine reference samples in the rows/columns <NUM>, <NUM> and then the predicted sample generation process such as a three-tap interpolation process is used on the combined values.

As discussed below in connection with <FIG>, this combination can be done "in advance" so that a first stage of operation of the intra predictor <NUM> can be to combine the multiple rows and columns of reference samples according to the currently selected prediction direction, so that that prediction sample generation process proceeds with respect to the combined values as though they were the reference samples themselves, providing an example in which in which the intra-image predictor is configured to combine the two or more parallel linear arrays of reference samples to form a linear array of reference samples.

Therefore, <FIG> provides an example in which the intra-image predictor is configured to combine two or more sets of reference samples (such as (a, c, e) and (b, d, f) in <FIG>, or (c, e, g) and (b, d, f) in <FIG>) to derive intermediate reference sample values (h, l, j), and to derive the predicted sample p from the intermediate reference sample values. In example arrangements, the intra-image predictor is configured to derive the predicted samples by interpolating amongst the intermediate reference samples. For example, each set of reference samples may comprises samples from a respective one or the two or more parallel arrays <NUM>, <NUM> of reference samples. In the case of the use of the samples (c, e, g) in <FIG>, based around the reference position <NUM>, this is an example in which each set of reference samples comprises a set, in the respective array of reference samples, pointed to by the prediction direction. In some examples, which the intra-image predictor is configured to combine the reference sample values according to a weighted combination, in which a weighting applied to a reference sample value decreases with increasing separation of the set of reference samples containing that reference sample value, from the current region or the current sample to be predicted. For example, the weighting of <NUM> can be used for the reference samples (b, d, f) from the array <NUM>, and the weighting <NUM> can be used for the reference samples (a, c, e) or (c, e, g) from the array <NUM>.

In alternative examples, rather than mixing c,b -> h a weighted mix (interpolation) of two or more of {a,c,e,g} can be used such that the interpolated value is spatially aligned with b according to the prediction direction <NUM>, Then h can be a <NUM>:<NUM> or other weighted mix between b and interp(two or more of {a,c,e,g}).

Effectively this involves interpolating the whole column <NUM> such that it is aligned with <NUM> according to the direction <NUM>. The interpolated column can then be mixed (by <NUM>:<NUM>, <NUM>:<NUM> or another weighting) with the column <NUM>.

During the interpolation process described above, since the projection of the column <NUM> to be spatially aligned with samples of the column <NUM> according to the current prediction direction will require interpolation, supersampling (so as to generate interpolated samples at a smaller spatial resolution than the original reference samples) could be used to reduce any negative impact of the interpolation process (since interpolation can in some situations soften data or reduces high frequency detail).

Another option is to use so-called non-uniform sampling, to combine the two columns into a supersampled data set. The phasing of the two regularly set of sampled values is determined by the angle of the currently selected prediction direction. To avoid effects of noise, the new reference samples may be low-pass filtered, either in a subsequent process, or as part of the supersampling process.

In another example method of operation, each row/column <NUM>, <NUM> is used individually to generate an intermediate predicted sample value, and the intermediate predicted sample values are then combined.

Therefore these arrangements provide examples in which each set of reference samples comprises a set, in the respective array of reference samples, or of values interpolated from the respective array of reference samples, pointed to by the prediction direction.

Looking first at <FIG>, this relates to the use of the range <NUM> in each row/column being aligned only with the reference position <NUM> in the row/column <NUM>, so that the reference samples a, c and e are combined (for example, by the three-tap interpolation process) to produce a first intermediate predicted sample p1. The reference samples b, d and f in the row/column <NUM> are combined by a similar process to produce a second intermediate predicted value p2. The values p1 and p2 can then be combined, for example, by an arithmetic mean or a weighted mean (for example, as discussed above, placing a greater weight such as <NUM> on the intermediate predicted sample value p2 and a reduced weight such as <NUM> on the intermediate predicted sample value p1, given that it is generated from reference samples further away from the block <NUM>) to generate the final predicted sample value p <NUM>.

A similar arrangement is shown in <FIG>, but making use of the range of reference samples <NUM> in the row/column <NUM> and the range <NUM> in the row/column <NUM>, which is to say that reference samples in the row/column <NUM> around the reference position <NUM> in that row/column are used.

So, the first intermediate predicted sample value p1 is generated from the reference samples c, e and g and the second intermediate predicted sample value p2 is generated from the reference samples b, d and f. As before, these can be combined by any of the processes discussed above to form the final predicted sample value p.

The examples discussed with reference to <FIG> relate to a pair of rows/column <NUM>, <NUM>. If more than two rows/columns are use, then either the processes discussed above could be applied individually. So, in the case of <FIG>, for n rows/columns, where n is at least two, all of the reference samples within respective ranges <NUM>, <NUM> and the like of each individual row/column are combined to form a set of three intermediate reference samples h, i, j which are then combined. In the case of <FIG>, for n rows/columns, where n is at least two, n intermediate predicted sample values are generated and are then combined, for example using a weighted combination.

In example arrangements, the controller <NUM> can vary the weighting according to one or more properties or parameters of the current interpolation process. For example, such a parameter may be the block size of the current block to be interpolated. The weighting could be detected by the controller <NUM> from a predetermined or programmable (for example via parameter sets communicated as part of the compressed data stream) set of weight values, or derived using a predetermined or programmable function. An example of such a relationship (whether defined by a look-up or a function) is:.

In other examples, the (or a) parameter may represent a spatial separation, in sample rows or columns or along the prediction direction, of the current sample to be interpolated from the nearest row/column of reference samples. In the example of <FIG>, the sample position <NUM> is in the fourth column of samples to be interpolated, starting at the reference column <NUM>. A mapping can be used between weightings and column separation (or row separation in the case of a generally vertical prediction direction, such as: m = weighting applied to nearer column / row of reference samples or to interpolated samples derived from them;.

The weighting used can be generated by applying two or more of these functions as discussed, for example with m,n being respective products of a weighting m,n derived by block size and a weighting m,n derived by sample position.

In other words, the influence or contribution of a non-adjacent row or column of reference samples increases as the separation of the sample position to be predicted from that row/column increases. For example, for samples to be predicted which are adjacent to the nearest row/column of reference samples, the influence of another (further away) row/column of reference samples may be expected to be lower than if the sample to be predicted is a long way (say, <NUM> pixels or more) from the row/column of reference samples adjacent to the current block, then the influence of the non-adjacent (such as next) row/column of reference samples may be expected to be larger.

Therefore, in examples, the intra-image predictor is configured to combine the intermediate sample values according to a weighted combination, in which a weighting applied to an intermediate sample value derived from reference samples non-adjacent to the current image region increases with increasing separation of the set of reference samples, from which that intermediate sample value as generated, from the current sample to be predicted.

In examples, the intra-image predictor is configured to combine the reference sample values according to a weighted combination, in which a weighting applied to a reference sample value non-adjacent to the current image region increases with increasing separation of the set of reference samples containing that reference sample value, from the current sample to be predicted.

Various different options of these combinations can be tested as trial encodings and one selected, for example according to a lowest sum of absolute differences (SAD) amongst those tested, for use in encoding, with the selection being indicated by parameter data communicated as part of the compressed data stream.

Alternatively reference samples in sub-groups in rows/columns could be combined using the techniques of <FIG> , to form sub-combinations which can then be processed using the techniques shown in <FIG>. An example of this arrangement is given below for an example arrangement of four rows/columns of reference samples, numbered <NUM>-<NUM>, where row/column <NUM> is spatially closest to the current block or region:.

Various options will now be discussed relating to the number of rows and columns of reference samples. Again, as before, the examples are discussed with relation to an 8x8 block <NUM> of samples to be predicted, but the same techniques are applicable to other sizes and/or shapes of blocks.

Note however that in some examples, certain block sizes and/or shapes may be excluded or restricted in their application of the present techniques, for example small blocks, such as blocks having either dimension equal to four samples or fewer.

Also, in the operation of an intra mode selector as discussed below, certain directional modes may be excluded from the present techniques.

Therefore, <FIG> provide examples in which the intra-image predictor is configured to derive the predicted samples by interpolating amongst one or more sets of reference samples. For example, the intra-image predictor can be configured to interpolate amongst two or more sets of reference samples (such as (a, c, e) and (b, d, f) in <FIG>, or (c, e, g) and (b, d, f) in <FIG>) to derive a respective intermediate sample value p1, p2 from each set of reference samples, and to combine the intermediate sample values to derive the predicted sample p. In example arrangements set of reference samples comprises samples from a respective one or the two or more parallel arrays <NUM>, <NUM> of reference samples. In the example of <FIG>, based around the reference positions <NUM>, <NUM>, each set of reference samples comprises a set, in the respective array of reference samples, pointed to by the prediction direction. As discussed above, the intra-image predictor <NUM> can be configured to combine the intermediate sample values according to a weighted combination, in which a weighting applied to an intermediate sample value decreases with increasing separation of the set of reference samples, from which that intermediate sample value as generated, from the current region (so that in the example given above, a weighting of <NUM> is applied to the closer array <NUM> and a weighting of <NUM> is applied to the further array <NUM>) or the current sample to be predicted.

<FIG> schematically illustrates a single row/column <NUM> of reference samples. If this was the only option available to the intra predictor, the operation would correspond to a previously proposed intra predictor, but the use of a single row/column <NUM> could be provided in an intra predictor forming an embodiment of the present disclosure in the context of its optional selection (by the intra mode selector) in combination with the optional selection (by the intra mode selector) of one or more other techniques shown in <FIG>.

<FIG> shows a pair of rows/columns <NUM>, <NUM> in which, as discussed above, the row/column <NUM> is extended by one or more samples <NUM>, <NUM> so as to allow for the use of the full range of prediction directions discussed above.

Similarly, <FIG> schematically represents three rows/columns of reference samples <NUM>, <NUM>, <NUM>. The row/column <NUM> is extended by one or more samples <NUM>, <NUM> with respect to the second row/column <NUM>, for the same reasons.

Finally as an example, although not representing a limit on the number of rows/columns which can be used, <FIG> schematically illustrates four rows/columns of reference samples, mainly rows/columns <NUM>, <NUM>, <NUM>, <NUM>. Once again, the row/column <NUM> is extended by one or more reference samples <NUM>, <NUM> with respect to the third row/column <NUM>, for the same reasons as those discussed above.

<FIG> show, for the example cases of <FIG> respectively, a projected version of the multiple rows/columns of reference samples (shown as shaded blocks in <FIG>). Note that in at least some examples, the projection process can be dependent upon the prediction direction in use, so a single example for an arbitrary prediction direction is employed in <FIG>. With respect to the projected reference sample, a similar technique employed to that in <FIG> can be used to derive reference positions and reference samples to apply the technique of <FIG>.

<FIG> schematically represents at least part of an operation of an intra mode selector such as the intra mode selector <NUM> of <FIG> described above.

The intra mode selector can operate to detect an appropriate mode for use in intra prediction of a current block or region with respect to a set of reference samples <NUM>. Various techniques have been proposed for achieving this, such as (at least partial) trial encoding and/or analysis of properties of the reference samples, to select the prediction operation amongst the candidate prediction operations.

In the present examples, any of these techniques can be used, with (in some example arrangements) the techniques being repeated, or applied in multiple instances, in respect of multiple permutations of the number of rows/columns of reference samples.

Here, the term "permutation" is used to indicate a group of rows/columns of reference samples. The group might include a row/column spatially nearest to the current block or region, and zero or more next-adjacent rows/columns each progressively spatially further away from the current block or region.

The term "prediction operation" can be used to describe a mode or direction and/or an associated permutation of rows/columns. Therefore, the intra-mode selector can, in example embodiments, be configured to select, from a set of candidate prediction operations each defining at least a prediction direction, a prediction operation for prediction of samples of a current region of a current image, the current region comprising an array of two or more rows and two or more columns of samples. The intra-image predictor is configured to derive predicted samples of the current region with respect to one or more of a group of reference samples of the same image in dependence upon a prediction direction, defined by the selected prediction operation, between a current sample to be predicted and a reference position amongst the reference samples. For at least some of the candidate prediction operations, the group of reference samples comprises two or more parallel linear arrays (such as rows, columns, rows and columns (noting that a row and column are still a linear array even with a "corner"), and/or projected arrays) of reference samples disposed at different respective separations from the current region.

The intra mode selector comprises a mode properties detector <NUM> which acts to detect the encoding properties of each mode under test (and, in at least some examples, of each mode with each permutation Pn of numbers n of rows/columns of reference samples available with that mode, where n ranges from <NUM> to a maximum limit of at least two). A coding efficiency detector <NUM> detects the coding efficiency for each mode/permutation tested by the mode properties detector <NUM>. The coding efficiency can relate to aspects such as the amount of data needed to encode the residual image which would arise where that mode and permutation of rows/columns to be used, along with the amount of data needed to signal the use of that mode/permutation.

In the selection of a prediction direction, example arrangements test all <NUM> directional modes with a simple SAD (sum of absolute differences) test to derive a shortlist of modes most likely to be useful for the current block. The shortlist of modes is then tested with a full encode to select a prediction mode for use.

The current techniques using multiple rows and/or columns of reference samples may in some situations be slower (or have higher processing requirements) than using a single row/column. To alleviate this at the encoder side where such a decision is made and then communicated to the decoder, example arrangements may be arranged to use the multi row/column prediction only for testing the shortlist of modes.

Based on the detection by the coding efficiency detector <NUM>, a mode selector <NUM> selects a prediction mode <NUM> to be sent to the intra predictor <NUM>, and information <NUM> is also sent to a mode encoder <NUM> such as a part of the controller <NUM> which encodes data <NUM> forming part of the encoded data stream indicating the mode/permutation in use, which is to say, data identifying the prediction operation selected for each region of the image.

Therefore, this provides an example in which the intra mode selector is configured to select amongst two or more groups of reference samples, each group comprising a respective different number of parallel arrays of reference samples.

<FIG> are respective schematic flow charts representing possible methods of operation of the intra mode selector of <FIG>.

In <FIG>, steps <NUM>. <NUM>, carried out in as many instances (whether in series, as schematically illustrated here, or in parallel) as there are available permutations P of rows/columns of reference samples, relate to the mode properties detector <NUM> and coding efficiency detector <NUM> detecting a best mode using each possible permutation of rows/columns of reference samples. So, a best mode may be selected using a single row/column of reference samples, another best mode may be selected using two rows/columns of reference samples and so on. Then, at a step <NUM>, the coding efficiency detector <NUM> detects the efficiencies of each of the modes and permutations detected at the step <NUM>. <NUM> so that at a step <NUM> the mode selector <NUM> selects a single mode and permutation of rows/columns and the mode encoder <NUM> encodes information defining the selected mode and permutation.

In an alternative mode of operation in <FIG>, an initial stage during the encoding process is to establish use of a particular permutation of n rows/columns (where n is at least two, so the permutation might be two rows/columns) and communicate this to the decoder in, for example, a parameter set, at a step <NUM>. Then, at a step <NUM>, the mode properties detector <NUM>, the coding efficiency detector <NUM> and the mode selector <NUM> cooperate to select a best prediction mode using the particular established permutation of rows/columns and at a step <NUM> the mode encoder <NUM> encodes information defining that mode.

At the decoder side, an intra mode selector is shown by way of example in <FIG>, comprising an encoded data detector <NUM> which detects data such as the data <NUM> in the encoded data stream defining a particular mode (and optionally a set of rows/columns) to be used, and a mode selector <NUM> provides information <NUM> to the intra predictor <NUM> indicating which mode and permutation of rows/columns to use, that is to say, it is configured to detect encoded data identifying the prediction operation selected for each region of the image.

<FIG> are respective flow charts schematically representing methods of operation of an intra predictor such as the intra predictor <NUM> of <FIG>.

<FIG> relates primarily to the operations shown in <FIG> above, in which, at a step <NUM>, an intermediate predicted sample value such as the intermediate predicted sample value p2 is interpolated from a first set of reference samples, for example the set in a closest row/column of reference samples to the current block or region, and then, using as many iterations as there are rows/columns of reference samples, a step <NUM> represents the interpolation of an intermediate predicted sample value p1 from each remaining set of reference samples from a respective row/column of reference samples. As discussed above, for those rows/columns of reference samples further away from the current block or region than the closest row/column of reference sample, the selection of which reference samples to use could be, for example, by detecting a reference position in each row/column according to the prediction direction or by using corresponding locations to those identified in the closest row/column. Then, at a step <NUM>, the intermediate predicted sample values are combined, for example by a weighted mean, to generate the final predicted sample value.

<FIG> relates more to the process shown in <FIG>, in which at a step <NUM>, respective members of the two or more sets of reference samples (with sets other than the set in the closest row/column being defined for example by tracking a further reference position along the prediction direction) into a combined set (h, i, j of <FIG>), and then interpolating a predicted sample value p from the combined set a step <NUM>.

As an optional feature of the operation of the intra predictor, <FIG> schematically illustrates a technique for providing the additional reference samples <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, or at least some of them, without necessarily having to simply repeat nearby or adjacent reference samples.

Referring to <FIG>, a missing reference sample detector <NUM> detects that a reference sample is not available. This could be because a sample at that position has not yet necessarily been decoded. In some examples, the sample has not been decoded. In other examples, a sample could have been decoded, but because it lies outside a current coding unit it could be that the hardware requirements such as buffering needed to make that reference sample available for the current prediction would be unreasonably high and so a design decision is taken such that the sample is not provided for prediction. For example, referring to <FIG>, these considerations may indicate that the samples <NUM>, <NUM>, <NUM> are not available if they are outside the current coding unit. To address these issues, in example arrangements an extrapolator <NUM> generates the required value <NUM> using an extrapolation process based on multiple ones of the available reference samples. Operation of this arrangement is shown by schematic flowchart of <FIG> in which a step <NUM> relates to the detection by the detector <NUM> of the missing reference samples and a step <NUM> relates to the extrapolation by the extrapolator <NUM> of the required values.

Further examples illustrating the use of missing reference sample detection will be discussed below.

<FIG> is a schematic flowchart illustrating an image encoding method comprising:.

In at least some of the example arrangements discussed above, the use of multiple rows or columns of reference samples may be constrained to instances where the "extra" (non-adjacent) rows or the multiple columns (or both) lie in the same coding tree unit as the current block. These conditions can be applied individually or together. Such arrangements will now be described further.

<FIG> schematically illustrates an array of coding units, in an example arrangement in which the image encoding apparatus is configured to encode the current image as successive coding units <NUM> of samples.

It will be appreciated from the discussion of <FIG> above that in at least some embodiments, coding takes place, coding unit by coding unit, from top left to bottom right of the set of coding units <NUM>. This means that for image regions at the extreme edges (the top edge and/or the left edge in this example) of a coding unit, it may be the case that at least some samples which would be required as reference samples in plural linear arrays as discussed above may or may not be available, depending on how much (if any) of a preceding decoded coding unit has been buffered. For example, for a particular coding unit <NUM>, prediction at the top <NUM> and/or the left <NUM> of the coding unit may be affected in this way. For coding units at the left and/or top of the image, the required reference sample data may not exist at all.

Note that the top left to bottom right encoding order is merely an example. If another order were used, the edges being considered here may be different to the top and left edges currently under discussion. Note also that the shape of the coding units shown in the schematic diagram of <FIG> may or may not be representative of the actual shape or relative sizes of the coding units.

<FIG> schematically illustrates a sample predictor <NUM>', similar to the intra-image predictor <NUM> of <FIG> but explicitly showing a sample store <NUM> to store samples corresponding to a region of the current image other than the current region. In particular, the sample store <NUM> can be arranged to store previously encoded and decoded samples from one or more coding units adjacent to the coding unit in which the current region is located, for use as reference samples in respect of (for example) an image region at a location within the current coding unit adjacent to a previous coding unit.

<FIG> schematically illustrate reference sample storage by the sample store <NUM>. In some examples, such as that shown schematically in <FIG>, the sample store <NUM> may be configured as a line store to store one or more lines or rows of previously encoded and decoded samples from a coding unit directly above a current coding unit <NUM>.

Here, it is noted that line stores are considered to be relatively "expensive", the term implying that they can require a significant amount of memory storage for their implementation, which can in turn require a significant amount of logic circuitry in, for example, an integrated circuit implementation of an encoder and/or decoder. The provision of line stores therefore represents a compromise between the potentially heavy requirements in terms of logic circuitry and the potential improvements in coding efficiency provided by the present techniques in which multiple rows and/or columns of reference samples may be used. Such reference samples may be readily available within a particular coding unit, but access to reference samples from outside the current coding unit can potentially be restricted by the implementation (or lack of implementation) of sample storage such as the sample store <NUM>.

In <FIG>, a column of samples <NUM> from a previously encoded and decoded coding unit to the left of the current coding unit <NUM> is stored for use as reference samples in respect of a left hand column of regions of the coding unit <NUM>.

It will be appreciated that the sample store <NUM> could store samples above (as in <FIG>) and to the left of (as in <FIG>) the current coding unit. It will be appreciated that one or more rows (and/or columns) of samples could be stored. It will be appreciated that a sample store <NUM> may not in fact be provided.

<FIG> schematically represents an intra mode selector arrangement of the type shown in <FIG>, except that the mode selector <NUM>' (similar in most respects to the mode selector <NUM>) is responsive to a detector <NUM> configured to detect whether samples corresponding to any of the two or more parallel linear arrays of reference samples are unavailable for use in prediction of samples of the current region and, if any of the two or more parallel linear arrays of reference samples are unavailable, to inhibit selection, by the intra mode selector <NUM>', of a candidate prediction operation dependent upon the unavailable reference samples.

Note that this can be a separate test and mechanism to the arrangement of <FIG>. In the present test, it is detected whether any of the two or more parallel linear arrays of reference samples are unavailable for example, because the current region is at a peripheral position with respect to a coding unit and/or image, and/or because any of the two or more parallel linear arrays of reference samples are not buffered (for example in line stores). A sample-by-sample extrapolation process of the type used in <FIG> is not applied, but instead, candidate prediction modes which use the unavailable rows/columns are inhibited from being selected.

Similarly, the detector <NUM> is further configured to detect for a current region of a current image which, if any, of the two or more parallel linear arrays are available for use in prediction of samples of the current region and to allow selection as a prediction operation, by the selector, of a candidate prediction operation dependent upon at least one of the available parallel linear arrays. Therefore in example embodiments the detector <NUM> allows or disallows the selection of modes by the selector <NUM>' in dependence upon whether, for the current image region, the required rows and/or columns of reference samples are available (for example, stored or buffered).

The detector <NUM> is in turn responsive to configuration data <NUM> defining the presence or absence of the sample store <NUM> and in particular defining how many (if any) rows and/or columns of samples of a previous adjacent coding unit it holds for use as reference samples in respect of image regions of the current coding unit.

Significantly, the configuration data <NUM> may define the lower of: (a) which stores are present at the decoder side and (b) which stores are available or present at the encoder side. This is because the selected mode will ultimately need to be implemented at the decoder, but the mode cannot be implemented in encoding unless the relevant stores are also present at the encoder side. If the encoded data is to be ultimately decoded by a known decoder, the properties of that decoder can be provided as the configuration data <NUM>. If however the decoder is unknown, then it may be that the configuration data <NUM> defines zero sample stores (even if one or more are present at the encoder) so as not to allow the generation of encoded data that cannot be decoded by an arbitrary decoder. In other examples, if a decoder standard, whether an official standard, a proprietary standard or a de facto industry standard, specifies that (for example) one line store (or a generic number n of line stores) must always be present, then for an unknown decoder the configuration data <NUM> can be arranged to specify n line stores, assuming that n line stores are available at the encoder.

In this way, the detector <NUM> can be responsive to configuration data defining one or more parameters of a decoding apparatus to detect whether samples corresponding to any of the two or more parallel linear arrays of reference samples will be available for use in prediction of samples of the current region at the decoding apparatus.

The detector <NUM> is also responsive to location information <NUM> defining the image location of the current image region with respect to the image and/or the current coding unit. If the current image region is adjacent a left or upper edge of the image then the detector can be configured to detect that multiple rows and/or columns of reference samples are unavailable. If the current image region is adjacent a left and/or upper edge of a coding unit, then the detector can be configured to detect that multiple rows and/or columns of reference samples are unavailable unless the configuration data <NUM> defines that such samples are held by sample stores <NUM>. Therefore, in these examples, the detector is configured to detect whether, for an image region at a location within a coding unit adjacent to a previous coding unit, any of the two or more parallel linear arrays of reference samples are held by the sample store.

<FIG> are schematic diagrams illustrating prediction processes, showing example operations of the detector <NUM> to detect whether the current region is adjacent an edge of the current region such that sample locations corresponding to at least some of the two or more parallel linear arrays of reference samples lie outside the current image. <FIG> and <FIG> illustrate prediction processes according to embodiments of the present disclosure. <FIG> and <FIG> illustrate prediction processes that are not according to the present disclosure and are present for illustration purposes only.

In <FIG>, an image region <NUM> being encoded or decoded is at the top of its respective coding unit. The boundary with the next-above coding unit is schematically represented by a bold line <NUM>. In this example instance a sample store <NUM> providing one line store is used, so that one line of samples from the next-above coding unit is available for use as reference samples. A second row of reference samples is not available above the image region <NUM>.

In <FIG>, a single row of reference samples is used for predictions involving a reference position amongst the reference samples above the image region <NUM>, such as a reference position <NUM>. However, because (in the example of <FIG>) two or more columns of samples <NUM> are available to the left of the region <NUM> for use as reference samples, predictions involving a reference position amongst the reference samples to the left of the image region <NUM>, such as a prediction represented by an arrow <NUM>, use two columns or linear arrays of reference samples.

In <FIG>, only a single linear array (row, column) is used for prediction for all reference sample locations so that a consistent technique is used in respect of all of the predictions. This is done even because the second row above is not available; even though the second column <NUM> is available it is unused.

In <FIG>, once again the current image region <NUM> is at the top of a coding unit (with the boundary <NUM> being shown by a bold line). In <FIG>, one line store is available, and in <FIG> two line stores are available.

In <FIG>, single row prediction is used for reference sample positions above the current image region <NUM> such as a reference sample position <NUM>, but for reference sample positions to the left, four column <NUM> prediction (using any of the techniques described above) can d be used. This applies to reference sample locations which do not use row data but only column data.

In <FIG>, an extra line store is used (or in other words, two line stores are provided) so a double row/column prediction is used for all sample locations. Although a third and fourth column <NUM> are available they are unused, so as to provide a consistent approach, although other examples could use two rows for reference sample positions above the current region and four columns for reference sample positions to the left of the current region.

Note that in all of the embodiments described here, for multiple rows/columns the prediction may be a weighted sum but this might be for example a <NUM>:<NUM>:<NUM>:<NUM> weighting rather than necessarily a <NUM>:<NUM>:<NUM>:<NUM> weighting (where the four weightings are in order of array separation from the current image region, for example, the first, second, third and fourth adjacent rows/columns). This could be implemented as a multiplexer.

Accordingly, in at least <FIG> and <FIG> the detector <NUM> is configured to detect, separately for reference sample positions disposed vertically or horizontally with respect to the current image region, whether samples corresponding to any of the two or more parallel linear arrays of reference samples are unavailable for use in prediction of samples of the current region (being, for example, all candidate prediction modes except those which rely on line stores or sample provision which are not present in respect of the current region) and, if any of the two or more parallel linear arrays of reference samples are unavailable for reference sample positions disposed vertically or horizontally with respect to the current image region, to inhibit selection, by the selector, of a candidate prediction operation dependent upon the unavailable reference samples. Note that the detection can take place region by region, since the presence or absence of line stores is generally relevant only to the top row of regions and/or to modes which rely on samples above the current region.

In the situation such as at the top of the image (as shown by <NUM> in <FIG>), regardless of what local buffering is present, samples above a current region may not be available simply because the current region is at the very top of the image. In such circumstances predetermined value (for example grey) samples can be substituted for the reference samples. The detector <NUM> can detect this situation from the location information <NUM> and control the detector <NUM> so as to disallow use of modes other than those which rely on the predetermined reference samples. Therefore in example embodiments, for at least some of the candidate prediction operations, the group of reference samples comprises one or more predetermined values; and the detector <NUM> is further configured to detect for a current region of a current image if none of the two or more parallel linear arrays is available for use in prediction of samples of the current region and to allow selection as a prediction operation, by the selector, of a candidate prediction operation for that current region dependent upon the predetermined values as reference samples.

At the decoder side, corresponding detections, derivations and control operations by the detector could be carried out, or alternatively the nature of the encoding could be communicated to the decoder in the same way as that described with reference to <FIG> described above.

<FIG> are schematic flowcharts illustrating respective methods.

<FIG> is a schematic flowchart illustrating an image decoding method comprising:.

Similarly, a data signal comprising coded data generated according to the methods discussed above (whether or not embodied on a non-transitory machine-readable medium) is also considered to represent an embodiment of the present disclosure.

Claim 1:
An image encoding apparatus comprising:
a selector (<NUM>') configured to select, from a set of candidate prediction operations each defining at least a prediction direction, a prediction operation for prediction of samples of a current region of a current image, the current region comprising an array of two or more rows and two or more columns of samples;
an intra-image predictor (<NUM>) configured to derive predicted samples of the current region with respect to one or more of a group of reference samples of the same image in dependence upon a prediction direction, defined by the selected prediction operation, between a current sample to be predicted and a reference position amongst the reference samples;
in which, for at least some of the candidate prediction operations, the group of reference samples comprises two or more adjacent linear arrays of reference samples disposed at different respective separations from the current region; and
a detector (<NUM>) configured to detect whether samples corresponding to any of the two or more adjacent linear arrays of reference samples are unavailable for use in prediction of samples of the current region and, if any of the two or more adjacent linear arrays of reference samples are unavailable, to inhibit selection, by the selector, of a candidate prediction operation dependent upon the unavailable reference samples;
in which the detector is configured to detect, separately for reference sample positions disposed vertically or horizontally with respect to the current image region, whether samples corresponding to any of the two or more adjacent linear arrays of reference samples are unavailable for use in prediction of samples of the current region and, if any of the two or more adjacent linear arrays of reference samples are unavailable for reference sample positions disposed vertically or horizontally with respect to the current image region, to inhibit selection, by the selector, of a candidate prediction operation dependent upon the linear array containing the unavailable reference samples.