Patent Description:
Perceptual transform coding of still images or videos is known to, for certain input, benefit from visual quantization models adhering to the characteristics of the human visual system (HVS) [<NUM>]. Especially in rate-constrained applications where the encoder must adjust the bit-rate of the coded stream dynamically [<NUM>], HVS motivated quantization typically allows to achieve a significantly increased subjective quality of the decoded content compared to objectively optimized quantization based on, e. , peak signal to noise ratio (PSNR) or mean-square error (MSE) measures. Recently, various subjectively optimized quantization methods have been presented. For example, HVS-based rate control based on [<NUM>] for video compression is described in [<NUM>], input adaptive quantization optimizing for a structural similarity measure (SSIM) is proposed in [<NUM>], a just-noticeable difference model simultaneously considering several psychovisual effects is utilized in [<NUM>], and subjectively tuned quantization is derived from a texture mask model in [<NUM>].

It is worth emphasizing that the abovementioned solutions tend to increase in algorithmic complexity over the years because their underlying models become more and more elaborate. As a result, their implementations into encoder software require an increasing amount of computational complexity, which slows down the encoding process. A low-complexity quantizer adaptation method is, thus, desirable.

In other words, it would be desirable to have a possibility at hand in order to control a coding quantization parameter locally across a picture in order adapt same to the picture content in a manner so as to improve or reduce the distortion at a given bitrate, for instance, by allowing for spending a finer quantization for areas of the picture perceptually liable to quantization errors, in favor of areas where the quantization may be made coarser owing the characteristics of the picture content of the latter areas to perceptually hide corresponding quantization errors. Additionally or alternatively, it would be favorable to have a concept at hand which allows for coding quantization parameters setting or control and allows for an easier implementation at comparable coding efficiency or vice versa improved coding efficiency at comparable implementation overhead with the coding efficiency, for instance, being determined in rate distortion sense.

It is, accordingly, the object of the present application to provide a concept for varying a coding quantization parameter across a picture which enables to obtain a more efficient coding of the picture if using the corresponding coding quantization parameter encoding the picture.

This object is achieved by the subject-matter of the independent claims of the present application.

In accordance with the present application, coding quantization parameter variation or adaptation is made more effective by basing the determination of a coding quantization parameter for a predetermined block of the picture on a dispersion of a statistical sample value distribution of a high-pass filtered version of the predetermined block. The usage of the high-pass filtered version of the predetermined block as a basis for the determination of the dispersion instead of using, for instance, the un-filtered or original version of the predetermined block assists in a better adaptation of the resulting coding quantization parameter variation across the picture to the human visual system. To be more precise, the high-pass filtering reduces the impact of object edges within the picture (also to be referred to as structural components) onto the determination of the coding quantization parameter or, differently speaking, focuses the responsiveness of the determination of the coding quantization parameter onto the noisy nature of the picture content (also to be referred to as textural components) which assists in perceptually hiding quantization errors.

In accordance with another non-claimed variant of the first aspect of the present application, which may be combined with the first one or be used separately, coding quantization parameter variation or adaptation across a picture is made more efficient using the following thoughts: The usage of a dispersion of a statistical sample value distribution of a predetermined block of a picture or a filtered version thereof in order to control the coding quantization parameter variation or adaptation across the picture allows for moderate implementation overhead and would thus, in principle, lend itself to control the coding quantization parameter variation/adaptation synchronously at both sides, i.e., encoder and decoder. An insight underlying the second variant of the first aspect of the present application is the fact that the inaccessibility of the dispersion for a block currently to be decoded for the decoder may be bypassed by using a spatially or temporally predicted dispersion at encoder and decoder, respectively, instead, or differently to determine the dispersion offset to the current block within a - in coding order - preceding portion in, for example, a spatial or temporal neighborhood, and use same instead of the dispersion of the actual current block being inaccessible for the decoder. In this regard, another insight of the non-claimed variant is the fact that the determination of a dispersion of a statistical sample value distribution of a certain block is sufficiently independent on being performed on a non-quantized version of the respective block or the quantized or reconstructable version of the block also being available at the decoder side as far as previously coded portions of the picture or the video to which the picture belongs are concerned. These thoughts and insights, in turn, end-up into a control of coding quantization parameter variation/adaptation across a picture in a manner which is still well-adapted to the human visual system although a predicted dispersion is used instead of a locally determined dispersion with enabling the coding quantization parameter variation/adaptation to be made deterministically dependent on previously coded portions so that the variation/adaptation may be synchronized between encoder and decoder and, in turn, any additional signalization overhead with respect to this variation/adaptation may be avoided.

In order to improve the coding efficiency in encoding a picture into a data stream, a comparison between a first coding quantization parameter assigned to a predetermined block of the picture and a threshold which depends on a mean difference of sample values of the predetermined block to sample values' mean value may be performed. This idea may be applied to embodiments of the first aspect and may form a basis of a non-claimed second aspect of the present application. The first coding quantization parameter is a kind of preliminary final version of the coding quantization parameter to be used for the predetermined block and the comparison acts as a kind of final check before actual usage of this coding quantization parameter: If the first coding quantization parameter deviates from the threshold towards a direction of coarser quantization, i.e., if the first quantization parameter results into a quantization step size larger than the threshold, the first coding quantization parameter is adjusted to obtain a second coding quantization parameter associated with a finer quantization than the first coding quantization parameter and the second coding quantization parameter is used in order to encode the picture rather than the first coding quantization parameter. If the first coding quantization parameter deviates from the threshold opposite to the direction of coarser quantization, the first coding quantization parameter may, for instance, be maintained and used to encode the picture. By using this final check the mechanism used to assign the first coding quantization parameter to the predetermined block of the picture may be designed in a manner which more aggressively tries to keep the quantization as coarse as possible because the final check avoids a too coarse quantization at blocks for which the coarseness would be exaggerated. The assignment of the first coding quantization parameter, in turn, may be made in any manner wherein some embodiments are described in the present application.

The non-claimed second aspect may be combined with the embodiments related to the first aspect. That is, coding quantization parameter variation or adaptation may be made more effective by basing the determination of a coding quantization parameter for a predetermined block of the picture on a dispersion of a statistical sample value distribution of a high-pass filtered version of the predetermined block. The usage of the high-pass filtered version of the predetermined block as a basis for the determination of the dispersion instead of using, for instance, the un-filtered or original version of the predetermined block assists in a better adaptation of the resulting coding quantization parameter variation across the picture to the human visual system. To be more precise, the high-pass filtering reduces the impact of object edges within the picture (also to be referred to as structural components) onto the determination of the coding quantization parameter or, differently speaking, focuses the responsiveness of the determination of the coding quantization parameter onto the noisy nature of the picture content (also to be referred to as textural components) which assists in perceptually hiding quantization errors.

Further, coding quantization parameter variation or adaptation across a picture may be made more efficient using the following thoughts: The usage of a dispersion of a statistical sample value distribution of a predetermined block of a picture or a filtered version thereof in order to control the coding quantization parameter variation or adaptation across the picture allows for moderate implementation overhead and would thus, in principle, lend itself to control the coding quantization parameter variation/adaptation synchronously at both sides, i.e., encoder and decoder. An insight is, as outlined above, the fact that the inaccessibility of the dispersion for a block currently to be decoded for the decoder may be bypassed by using a spatially or temporally predicted dispersion at encoder and decoder, respectively, instead, or differently to determine the dispersion offset to the current block within a - in coding order - preceding portion in, for example, a spatial or temporal neighborhood, and use same instead of the dispersion of the actual current block being inaccessible for the decoder. In this regard, another insight is, as outlined above, the fact that the determination of a dispersion of a statistical sample value distribution of a certain block is sufficiently independent on being performed on a non-quantized version of the respective block or the quantized or reconstructable version of the block also being available at the decoder side as far as previously coded portions of the picture or the video to which the picture belongs are concerned. These thoughts and insights, in turn, end-up into a control of coding quantization parameter variation/adaptation across a picture in a manner which is still well-adapted to the human visual system although a predicted dispersion is used instead of a locally determined dispersion with enabling the coding quantization parameter variation/adaptation to be made deterministically dependent on previously coded portions so that the variation/adaptation may be synchronized between encoder and decoder and, in turn, any additional signalization overhead with respect to this variation/adaptation may be avoided.

In accordance with a non-claimed third aspect, the present application is based on the finding that rendering coding quantization parameter adaptation dependent on an evaluation of samples enables to render multi-channel encoding more efficient in terms of complexity and/or may relax the side information overhead in conveying information on the coding quantization parameter such that it is leads to an efficiency increase when coding a multi-channel picture and applying the coding quantization parameter adaptation channel-specifically.

The non-claimed third aspect is also combinable with the embodiments of the first aspect. For example, coding quantization parameter adaptation may be made by evaluating the sample activity. A dispersion of a statistical sample value distribution of a non-filtered or a high-pass filtered version of the predetermined block may be used. The usage of the high-pass filtered version of the predetermined block as a basis for the determination of the dispersion instead of using, for instance, the un-filtered or original version of the predetermined block may lead to a better adaptation of the resulting coding quantization parameter variation across the picture to the human visual system. To be more precise, the high-pass filtering reduces the impact of object edges within the picture (also to be referred to as structural components) onto the determination of the coding quantization parameter or, differently speaking, focuses the responsiveness of the determination of the coding quantization parameter onto the noisy nature of the picture content (also to be referred to as textural components) which assists in perceptually hiding quantization errors. When so done for each channel, the resulting coding quantization parameters derived from the activity measured in high-pass filtered domain results into efficient coding of each channel thereby leading to increased coding efficiency of a multi-channel picture.

Further, when rendering coding quantization parameter adaptation across a picture dependent on a channel-wise evaluation of the sample activity, the multi-channel coding may be rendered more efficient based on the following thoughts: The usage of a dispersion of a statistical sample value distribution of a predetermined block of a picture or a filtered version thereof in order to control the coding quantization parameter variation or adaptation across the picture allows for moderate implementation overhead and would thus, in principle, lend itself to control the coding quantization parameter variation/adaptation synchronously at both sides, i.e., encoder and decoder. The inaccessibility of the dispersion for a block currently to be decoded for the decoder may be bypassed by using a spatially or temporally predicted dispersion at encoder and decoder, respectively, instead, or differently to determine the dispersion offset to the current block within a - in coding order - preceding portion in, for example, a spatial or temporal neighborhood, and use same instead of the dispersion of the actual current block being inaccessible for the decoder. Favorably, the determination of a dispersion of a statistical sample value distribution of a certain block is sufficiently independent on being performed on a non-quantized version of the respective block or the quantized or reconstructable version of the block also being available at the decoder side as far as previously coded portions of the picture or the video to which the picture belongs are concerned. These thoughts and insights, in turn, end-up into a control of coding quantization parameter variation/adaptation across a picture in a manner which is still well-adapted to the human visual system although a predicted dispersion is used instead of a locally determined dispersion with enabling the coding quantization parameter variation/adaptation to be made deterministically dependent on previously coded portions so that the variation/adaptation may be synchronized between encoder and decoder and, in turn, any additional signalization overhead with respect to this variation/adaptation may be avoided. Using this control channel-individually enables a highly efficient multi-channel picture coding.

In patent publication <CIT>, a macro-block is high pass filtered to determine the activity of the macro-block. Based on the determined activity, a block is classified as a smooth, edge or texture macro-block and quantized according to its classification.

Advantages implementations are the subject of dependent claims. Preferred embodiments of the present application are described with respect to the figures among which:.

In the following, various embodiments for varying or adjusting a coding quantization parameter are described. These embodiments use at least one of the aspects highlighted above or a combination thereof. Before discussing these embodiments, however, some thoughts shall be presented here which led to the aspects which the embodiments described later on make use of. In particular, it has been noticed that, of the psychovisual effects commonly exploited in the literature, namely,.

only the second category is viewer and environment invariant. To be precise, the frequency or contrast sensitivity depends on factors such as the viewing distance to, and resolution of, the display depicting the decoded image or video, and higher-level HVS factors highly depend on the picture region the observer is looking at [<NUM>] (humans only possess high visual acuity over a small viewing area called the fovea). In practice, a viewer is often given control over the video playback speed - up to the point of pausing the video or taking still snapshots of certain frames - and can look at the image or video repeatedly and focus on any spatial (or temporal) region thereof. Hence, it can be concluded that such HVS characteristics cannot be exploited reliably in an image or video encoder.

Given the introduced requirements of low computational complexity and high viewer and environment invariance in a visually optimized quantization approach the embodiments described hereinafter seek to enable simple implementations thereof. In particular, some embodiments for coding quantization parameter variation/adaptation use an aspect according to which same is performed in a manner dependent on a dispersion of a statistical sample value distribution of a high-pass filtered version of a predetermined block. A block-wise determined measure is used in [<NUM>] and its extension described in [<NUM>], where both are luminance based, i.e., do not incorporate any available chrominance channels into the analysis. Owing to the determination of the dispersion measure on the basis of the high-pass filtered version, some embodiments described hereinafter result into improved coding efficiency and/or lower implementation overhead. For instance, unlike the approaches of [<NUM>] and [<NUM>] which involve regional classifications of each picture into either smooth/flat, edge, or texture blocks, the embodiments of the present application avoid such classification or render it superfluous. Some of these embodiments or other embodiments of the present application avoid an overhead for controlling the coding quantization parameter variation/adaptation by using a predicted dispersion instead of a locally determined dispersion measure, thereby lowering the coding rate at improved adaptation to the human visual system. Even further ones of these embodiments or other embodiments not part of the invention described hereinafter use a kind of suitability check for a coding quantization parameter by comparing the exceeding or succeeding a certain threshold to determine whether the coding quantization parameter preliminary assigned to a certain predetermined block results into a too coarse quantization in which even the coding quantization parameter is adjusted to render the quantization finer.

In the following, an embodiment of the present application is described which performs coding quantization parameter variation/ adaptation across a picture in a manner dependent on a dispersion of a statistical sample value distribution.

This embodiment is exemplified as a possible modification of the HEVC codec by way of concrete examples, for instance, the dependency of the coding quantization parameter of the thus-determined dispersion, the dispersion measure itself and/or the relationship between the coding quantization parameter and the quantization step-size parametrized thereby, but it is clear that all these details may likewise be applied to any other video or picture codec. Accordingly, at the end of this description, there follows a presentation of embodiments which transfer this specific embodiment onto a less specific coding environment.

With respect to the non-claimed third aspect with respect to which embodiments are subsequently described which perform coding quantization parameter variation/adaptation across a multi-channel picture channel-individually such as for luma separately as done for chroma, by evaluating, separately, samples of the respective channel with the activity possibly being used as a basis, and with possibly using any dispersion measure to measure the activity, description brought forward below first, explains the underlying concepts without consideration of the juxta-position of channels. Rather the QP adaptation functionality is firstly described for mono-channel environments. That is, with respect to the third aspect, the just following description represents comparison examples. And in doing so, i.e. in providing comparison examples, the explanation starts with encoder only related aspects, whereinafter QP adaptation functionalities are described which are applicable to encoder and decoder and may be used to substitute, at least partially, any side information overhead in synchronizing QP adaptation between encoder and encoder. Performing coding quantization parameter variation/adaptation across a picture in a manner dependent on a dispersion of a statistical sample value distribution of a high-pass filtered version is exemplified in the following as a possible modification of the HEVC codec by way of concrete examples for the high-pass filtering, for instance, the dependency of the coding quantization parameter of the thus-determined dispersion, the dispersion measure itself and/or the relationship between the coding quantization parameter and the quantization step-size parametrized thereby, but it is clear that all these details may likewise be applied to any other video or picture codec. As already stated, at the end of this description, there follows a presentation of embodiments which transfer this specific embodiment onto a less specific coding environment.

All contemporary perceptual image and video transform coders apply a quantization parameter (QP) for rate control which, in the encoder, is employed as a divisor to normalize the transform coefficients prior to their quantization and, in the decoder, to scale the quantized coefficient values for reconstruction. In High Efficiency Video Coding (HEVC) as specified in [<NUM>], the QP value is coded either once per image or once per N × N block, with N = <NUM>, <NUM>, <NUM>, or <NUM>, on a logarithmic scale with a step-size of roughly one dB: <MAT> where q is the coded QP index and ' indicates the reconstruction. Notice that QP' is also utilized in the encoder-side normalization to avoid any error propagation effects due to the QP quantization. The present embodiment adjusts the QP locally for each <NUM> × <NUM>-sized coding tree unit (CTU, i. , N = <NUM>) in case of images and videos with a resolution equal to or less than Full High Definition (FHD, <NUM> × <NUM> pixels), or for each <NUM> × <NUM> or <NUM> × <NUM>-sized block in case of greater-than-FHD resolution (e. , <NUM> × <NUM> pixels). For each of these block units, two spatially filtered variants of the picture's luminance (luma, Y) components are derived as follows:
<MAT>
<MAT>
with µ = Σx,y ∈b p(x,y)/N<NUM> being the average DC component of the given N × N-sized block b and x, y representing the horizontal and vertical coordinates, respectively, of each luma pixel p inside said block, i. , x, y ∈ b. Then, from both the high-pass filtered pixels ṕ(x,y) in (<NUM>) and the DC compensated (zero-mean) low-pass pixels p(x,y) in (<NUM>), the block-wide normalized L<NUM> or L<NUM> norm is obtained:
<MAT>.

The squares of these L<NUM> or L<NUM> norms are averaged across the entire picture (or slice, in case of HEVC), which for the L<NUM> norm implies that said square cancels the square-root in (<NUM>). In a FHD picture, <NUM> per-b Ṕ<NUM> or <NUM> and Ṕ<NUM> or <NUM> values, abbreviated as Ṕ and Ṗ hereafter (hence dropping the subscripts), are averaged when N = <NUM>. Using <MAT> for logarithmic conversion, which can be implemented efficiently using table look-ups (see, e. , [<NUM>] for a general algorithm), a QP offset -q < ob ≤ <NUM>-q for each block b can, finally, be determined: <MAT> with a = ¼. In HEVC, this CTU-wise offset is added to the default slice-wise QP index q, and QP' for each CTU is obtained from (<NUM>).

Note that, to slightly reduce the delta-QP side-information rate, it was found to be advantageous to apply two-dimensional median filtering to the resulting matrix of q + ob sums transmitted to the decoder as part of the coded bit-stream. In the preferred embodiment, a three-tap cross-shaped kernel, i. , a filter computing the median for a value from that value and its immediate vertical and horizontal neighbors, similar to the high-pass filter of (<NUM>), is used. Moreover, in each CTU, the rate-distortion parameter λb needs to be updated according to q + ob to maximize the coding efficiency <MAT>.

In [<NUM>], edge blocks were classified into a separate category and quantized using dedicated custom parameters in order to prevent a noticeable increase in quantization-induced ringing effects around straight directional lines or object borders. When using the current embodiment in the context of HEVC, no such effects can be observed even though no comparable classification is performed. The most likely reason for this property is the increased efficiency of HEVC over the MPEG-<NUM> standard used in [<NUM>] with regard to edge coding. Most notably, HEVC supports smaller <NUM> × <NUM> blocks, with optional transform skipping for quantization directly in the spatial domain, as well as a Shape Adaptive Offset (SAO) post-filtering operation to reduce banding and ringing effects during decoding [<NUM>, <NUM>].

Thanks to the incorporation of the picture-averaged avg(Ṗ<NUM>) and avg(Ṕ<NUM>) in (<NUM>), the average coding bit-rate, when measured across a diverse set of input material, does not increase significantly due to the application of the QP adaptation proposal. In fact, for q = <NUM> and similar nearby values, the mean bit-stream rate was found not to change at all when employing the QP adaptation. This property can, therefore, be regarded as a second advantage of the present embodiment, aside from its aforementioned low computational complexity.

It should be emphasized that the present embodiment can easily be extended to non-square coding blocks. As should be evident to those skilled in the art, unequal horizontal and vertical block/CTU sizes can be accounted for in (<NUM>-<NUM>) by replacing all occurrences of (here: divisions by) N<NUM> with (divisions by) N<NUM> · N<NUM>, where the subscripts <NUM> and <NUM> denote the horizontal and vertical block dimensions.

After having described first embodiments using a dispersion of a statistical sample value distribution of a block to control the coding quantization parameter for this block, a corresponding embodiment is described in the following with respect to <FIG> which shows an apparatus for varying or adapting a coding quantization parameter across a picture and its possible applicability in an encoder for encoding a picture, but this time the details presented above are generalized and although the embodiment of <FIG> may be implemented as a modification of a HEVC codec as it has been the case above, this needs not to be necessarily the case as outlined in more detail below.

<FIG> shows the apparatus <NUM> for varying the coding quantization parameters QP across a picture <NUM> as comprising a dispersion determiner <NUM> and a QP determiner <NUM>. The dispersion determiner determines a dispersion of a statistical sample value distribution of a high-pass filtered version of a predetermined block of picture <NUM>. The dispersion determiner <NUM> computes the dispersion, for instance, using the above-mentioned equation <NUM>, i.e., may use a Lp norm with p ≥ <NUM>. Further, as also discussed above, the dispersion determiner <NUM> subjects the predetermined block to the high-pass filtering first followed by the determination of the dispersion <NUM> by computing a dispersion of a statistical distribution of the thus high-pass filtered sample values. The high-pass filtering may be performed using an FIR filter such as, for instance, according to equation <NUM> where each high-pass filtered sample value x, y is a sum, or depends on a sum, of the co-located sample value (px,y) times a first weight in sample values especially neighboring the respective sample value times second weights differing in sign to the first weight. Although a cross-shaped filter kernel, i.e., the respective filtered sample position and for surrounding neighboring sample positions, is used according to equation <NUM>, the high-pass filtering may, naturally, be embodied differently. Likewise, the weights, i.e., <NUM> and - <NUM>, according to equation <NUM> may be selected differently, too. As far as the dispersion is concerned, dispersion determiner <NUM> may use a Lp norm where p = <NUM> or p = <NUM> to measure the dispersion, as done according to equation <NUM>, but dispersion determiner <NUM> may alternatively use other measures of dispersion such as the in-terquartile range which is not part of the invention or any other Lp norm suitably measuring the dispersion, i.e., the scatter or spread of the sample values within the predetermined block.

The QP determiner <NUM> receives the dispersion <NUM> and, depending thereon, determines the quantization parameter QP. As described above, the QP determiner <NUM> subjects the dispersion received from dispersion determiner <NUM> to logarithmization such as indicated in equation <NUM> although any other transition to logarithmic domain may be used alternatively.

In addition to the just-discussed high-pass filter domain dispersion, dispersion determiner <NUM> further determines a further dispersion of a statistical sample value distribution of a low-pass filtered version of the predetermined block with the QP determiner <NUM> performing the determination of QP further depending on the latter dispersion. For instance, the low-pass filtering may be performed using an FIR filter and in particular using, for instance, the equation <NUM> discussed above although different ratings of the summation of the sample values within the filter kernel or a differently shaped filter kernel may be used alternatively. As to the actual dispersion measure used, the same as discussed above with respect to the high-pass filter domain dispersion applies, i.e., a Lp norm with p ≥ <NUM> may be used, for instance, or any other dispersion measure. The QP determiner <NUM> may apply a logarithmization to the low-pass filter domain dispersion and QP determiner <NUM> may form a weighted sum between both dispersions in order to obtain the quantization parameter such as equation <NUM>. The determination by QP determiner <NUM> may also involve a rounding or a quantization as indicated in equation <NUM>, i.e., a rounding of the dispersion in logarithmic domain, for instance.

The mode of operation of dispersion determiner <NUM> and QP determiner <NUM> has been discussed above with respect to a certain predetermined block of picture <NUM>. Such a predetermined block is exemplarily indicated in <FIG> at 20a, for instance. In the manner just-outlined, determiner <NUM> and determiner <NUM> act on each of a plurality of blocks picture <NUM> is composed of, thereby achieving the QP variation/adaption across picture <NUM>, i.e., the adaptation of the quantization parameter QP to the picture content so as to be adapted to the human visual system, for instance.

Due to this adaptation, the resulting quantization parameter may advantageously be used by an encoding stage <NUM> receiving the corresponding quantization parameter QP in order to encode the corresponding block of picture <NUM> into a data stream <NUM>. Accordingly, <FIG> exemplary shows as to how apparatus <NUM> may be combined with an encoding stage <NUM> so as to result into an encoder <NUM>. The encoding stage <NUM> encodes picture <NUM> into a data stream <NUM> and uses, to this end, the quantization parameter QP varied/adapted by apparatus <NUM> across picture <NUM>. That is, within each block, which picture <NUM> is composed of, encoding stage <NUM> uses the quantization parameter as determined by QP determiner <NUM>.

For sake of completeness, it should be noted that the quantization parameter used by encoding stage <NUM> to encode picture <NUM> may not solely be determined by QP determiner <NUM>. Some rate control of encoding stage <NUM>, for instance, may cooperate to determine the quantization parameter such as, for instance, by determining QPq while the contribution by QP determiner <NUM> may end-up into QP offset <NUM>b. As shown in <FIG>, encoding stage <NUM> may, for instance, code the quantization parameter into data stream <NUM>. As described above, a quantization parameter may be coded into data stream <NUM> for the corresponding block such as block 20a in logarithmic domain. The encoding stage <NUM>, in turn, may apply the quantization parameter in the non-logarithmic domain, namely in order to normalize the signal to be coded into data stream <NUM> by using the quantization parameter in non-logarithmic or linear domain as a divisor applied to the respective signal. By this measure, the quantization noise resulting from the quantization by encoding stage <NUM> is controlled across picture <NUM>.

The encoding of the quantization parameter into the data stream <NUM> may, as discussed above, be made as differences to a base quantization parameter of larger scope globally determined, for instance, for picture <NUM> or slices thereof, i.e., in form of offsets Ob and the coding may involve entropy coding and/or differential or predictive coding, merging or similar concepts.

Owing to the fact that the dispersion <NUM> is determined for a high-pass filtered version of a block, the dispersion <NUM> is well-suited to adapt the quantization parameter to the HVS. Block 20a of <FIG>, for instance, is illustrated as covering picture content of picture <NUM> relating a treetop. Owing to the leaves of the tree, the dispersion will be relatively high. This dispersion may, thus, be used to set the quantization QP relatively high for this block as the non-smooth or non-flat leaf texture of the tree hides for the human eye any coding error owing to quantization errors. <FIG> representatively shows another block 20b, this time relating to the side of a van which might be monochrome or at least large monochrome areas (i.e. has a smooth or flat texture). Here, the dispersion will be relatively low and in fact, quantization errors might here be liable to perception. Even if block 20b crosses an edge of one monochrome area to another (i.e. contains structural components), then the high-pass filter domain within which the dispersion <NUM> is determined results in dispersion <NUM> being relatively low so that, still, coding errors may be avoided here.

For sake of completeness, <FIG> shows a possible structure of encoding stage <NUM>. In particular, <FIG> relates to the case where encoder <NUM> of <FIG> is a video coder with picture <NUM> being one picture out of a video <NUM>. Here, the encoding stage <NUM> uses hybrid video coding. Encoding stage <NUM> of <FIG> comprises a subtractor <NUM> to subtract a prediction signal <NUM> from the signal to be coded, such as picture <NUM>. In a concatenation of an optional transform stage <NUM>, a quantizer <NUM> and entropy coder <NUM> are connected in the order of their mentioning to the output of subtractor <NUM>. Transformation stage <NUM> is optional and may apply a transformation, such as s spectrally decomposing transformation, onto the residual signal output by subtractor <NUM> and quantizer <NUM> quantizes the residual signal in transform domain or in spatial domain on the basis of the quantization parameter as varied or adapted by apparatus <NUM>. The thus quantized residual signal is entropy encoded into the data stream <NUM> by entropy encoder <NUM>. A concatenation of a dequantizer <NUM> followed by an optional inverse transformer <NUM> reverses or performs the inverse of the transform and quantization of modules <NUM> and <NUM> so as to reconstruct the residual signal as output by subtractor <NUM> except for the quantization errors occurring owing to the quantization by quantizer <NUM>. An adder <NUM> adds the reconstructed residual signal and the prediction signal <NUM> to result into a reconstructed signal. An in-loop filter <NUM> may optionally be present in order to improve the quality of completely reconstructed pictures. A prediction stage <NUM> receives reconstructed signal portions, i.e., already reconstructed portions of a current picture and/or already reconstructed previously coded pictures, and outputs the prediction signal <NUM>.

<FIG>, thus, renders clear that the quantization parameter as varied or adapted by apparatus <NUM> may be used in the encoding stage <NUM> so as to quantize a prediction residual signal. The prediction stage <NUM> may support different prediction modes such as an intra prediction mode according to which prediction blocks are spatially predicted from already coded portions, and an inter prediction mode according to which a prediction block is predicted on the basis of already coded pictures such as a motion-compensative prediction mode. It should be noted that the encoding stage <NUM> may support switching on/off the residual transform by transformation stage <NUM> and the corresponding inverse transformation by inverse transformer <NUM> in units of residual blocks, for instance.

And further, it should be noted that the block granularities mentioned may differ: the blocks at which the prediction mode is varied, the blocks at which prediction parameters for controlling the respective prediction mode are set and transmitted in data stream <NUM>, the blocks at which transformation stage <NUM> performs individual spectral transforms, for instance, and finally, the blocks 20a and 20b at which the quantization parameter is varied or adapted by apparatus <NUM> may mutually differ or at least some may differ mutually. For instance, and as exemplified in the above example with respect to HEVC, the sizes of blocks 20a and 20b at which the quantization parameter variation/adaptation by apparatus <NUM> is performed, may be more than four times larger than a smallest block size at which the transforms by transformation stage <NUM> are performed when the spectral transform may, for instance, be a DCT, DST, KLT, FFT or a Hadamard transform. It may alternatively even be larger than eight times the minimum transform block size. As indicated above, the in-loop filter <NUM> may be an SAO filter [<NUM>]. Alternatively, an ALF filter may be used [<NUM>]. Filter coefficients of the in-loop filter may be coded into data stream <NUM>.

Finally, as has already been indicated above, the QPs as output by apparatus <NUM> may be coded into the data stream in a manner having passed some two-dimensional median filtering so as to lower the necessary data rate.

For sake of completeness, <FIG> shows a possible decoder <NUM> configured to decode from data stream <NUM>, a reconstructed version <NUM> of video <NUM> and/or picture <NUM>. Internally, this decoder comprises an entropy decoder <NUM> at the input of which the data stream <NUM> enters, followed by modules shown, and interconnected to each other in a manner shown, with respect to <FIG> so that the same reference signs have been used in <FIG> again, with an apostrophe, however, in order to indicate their presence in decoder <NUM> instead of encoder stage <NUM>. That is, at the output of adder <NUM>' or, optionally, the output of in-loop filter <NUM>' the reconstructed signal <NUM> was obtained. Generally speaking, a difference between modules of encoding stage <NUM> of <FIG> and decoder <NUM> of <FIG> relies on the fact the encoding stage <NUM> determines or sets in accordance with some optimization scheme using, for instance, a Lagrangian cost function, depending on rate and distortion, the prediction parameters, prediction modes, the switching between residual transform of remaining and spatial domain for residual coding and so forth. Via data stream <NUM>, the quantizer <NUM>' obtains the quantization parameter variation/adaptation favorably chosen by apparatus <NUM>. It uses the quantization parameter in the non-logarithmic domain as a factor in order to scale the quantized signal, namely the quantized residual signal obtained by entropy decoder <NUM> from data stream <NUM>. The just-mentioned Lagrangian cost function may involve a Lagrangian rate/distortion parameter which is a factor applied to the coding rate with the corresponding product being added to the distortion to result into the Lagrangian cost function. This Lagrangian rate/distortion parameter may be adapted by the encoding stage <NUM> depending on the coding quantization parameter as described above with respect to equation <NUM>.

In the following, a further embodiment of the present application is presented, called implicit visual QP adaptation (IV-QPA). Again, this embodiment is presented as a possible modification of HEVC with specific details presented. Thereinafter, broadening embodiments are described.

In case of block-wise QP adaptation according to, e. , the previously described embodiment, the adjusted QP indices are coded differentially, usually with subsequent entropy coding (e.g., binary arithmetic coding), and multiplexed into the coded image or video bit-stream. An alternative to this explicitly signaled, visually motivated QP adaptation is an implicit visual QP adaptation (IV-QPA) approach in which the adapted QP index qb for each block b is not transmitted as part of the bit-stream but synchronously determined and applied at both the encoder and decoder side from existing bit-stream data. More specifically, each qb (current QP index) may be derived from the previously decoded and reconstructed image or video picture in the spatially adjacent left, above, and (optionally) above-left neighboring areas, as illustrated in <FIG>. Notice that said neighboring blocks have been reconstructed using associated QP indices qa (above) and ql (left) which, in turn, may have been derived from respective neighboring reconstructed picture data.

The motivation behind the IV-QPA approach is the observation that, at all but very low image/video coding bit-rates, the decoded and reconstructed picture content closely approximates the initial input content and, as such, is equally well suited for visually motivated local QP adaptation (assuming the N × N block size associated with each QP is not too small). It can, therefore, be concluded that the additional codec bit-rate typically required for conveying explicitly signaled block-wise adapted QP indices (which reaches up to roughly <NUM> % of the total bit-rate at typical operating points) can be saved. In fact, informal experiments revealed that IV-QPA can, in terms of perceptual performance (i. , visual quality gain), match existing explicit QP adaptation according to, e. , the previously described embodiment. However, for correct operation and minimal algorithmic complexity overhead at the decoder side (the IV-QPA method must, as noted, be carried out in both the encoder and decoder), two slight modifications to the algorithm calculating the ob offset for each block are required, as described hereafter. As earlier, the inventive method is, preferably, integrated into a block-based image or video transform coding design such as HEVC [<NUM>].

Given the spatial QP resolution as an aforementioned block size N × N, identically predefined in both the encoder and decoder, the IV-QPA method is controlled by an existing picture-wise (or, in a HEVC based codec, a slice-wise) "global" QP index q as mentioned above. To obtain the "local" QP offset ob for each block b, corresponding offsets oa, and ol are determined for the above and left neighboring blocks of b, respectively, if applicable. Specifically, if a decoded, reconstructed instance of the luma picture component, with pixels p, is available for the left neighbor (i. , block b is not located at a left picture/slice boundary), ṕ(x,y) are computed via (<NUM>) for all x, y belonging to said left neighboring block. These high-pass filtered values are then used to obtain Ṕ<NUM> or <NUM> (abbreviated as Ṕl) according to (<NUM>) and, subsequently, its logarithmic representation L(Ṕl) using (<NUM>). If, analogously, a decoded, reconstructed instance of the luma picture is available for the above neighboring block (i. , b is not located at a top picture/slice boundary), ṕ(x,y) are obtained for all x, y belonging to said above block. These values are used to derive Ṕa via (<NUM>) and L(Ṕa) via (<NUM>). Note that the same procedure can be employed to compute the low-pass counterparts L(Ṕl) and L(Ṕa) as in the previous description, but to minimize the computational workload especially at the decoder side, this is omitted in the present embodiment.

Having determined L(Ṕl) and L(Ṕa), but not L(Ṕl) and L(Ṕa), the "local" QP offset ob for the current block b can then be derived as follows. If neither L(Ṕl) nor L(Ṕa) are available, then op = <NUM>, i. If only L(Ṕl) is available, then ob = d + L(Ṕl), where d is a constant which depends on the picture dimensions or the "global" q (for example, d = ((<NUM><NUM> + PictureWidth · PictureHeight) >> <NUM>) + (q >> <NUM>) - <NUM>, with ">>" denoting an integer right-shift). Likewise, if only L(Ṕa) is available, then ob = d + L(Ṕa), using the same d. If, however, both the left and above neighboring values are available, then ob = d + (L(Ṕl) + L(Ṕa)) / <NUM>, and qb = q + ob. As described above, the reconstructed QP' for each block b is obtained using (<NUM>), and used in both the encoder (for normalization) and decoder (for scaling).

Algorithmically, (<NUM>) is the most complex part of IV-QPA. However, it is worth noting that L(Ṕl) of a certain block b<NUM> in the previous picture row and L(Ṕa) of some block b<NUM> in the current picture row are computed on partially overlapping picture data. Hence, by saving the partial result of said L(Ṕl) operation for b<NUM> for the overlapping picture region and subsequently reusing said partial result during the computation of L(Ṕa) for b<NUM> in said current picture row, as depicted in <FIG>, an overall reduction in the computational complexity of the present IV-QPA embodiment can be achieved. Note that, when the optional above-left neighboring M<NUM> × N<NUM>-sized region C of <FIG> is employed in the IV-QPA process, the shared partial result of the L(Ṕ. ) calculations for blocks b<NUM> and b<NUM> equals the result of the L(Ṕ. ) calculation for the above-left area C for the right-hand neighbor of block b<NUM>, herein called b<NUM>, processed after b<NUM>. Thus, as shown in <FIG>, the L(Ṕ. ) result for region C does not need to be computed for block b<NUM> as it is already available.

Revisiting <FIG>, three further specifics shall be discussed. First, like the explicit QPA embodiment described previously, the IV-QPA scheme is generalized to allow for unequal horizontal and vertical block or CTU dimensions. This is illustrated by the separate definitions for the block/CTU width N<NUM> and height N<NUM> as a straightforward generalization of the N × N block/CTU size, which should be apparent to those skilled in the art. Second, <FIG> visualizes that the neighboring above, left, and above-left picture areas (A, B, and C, respectively) adjacent to the current picture block b may be, but do not necessarily need to be, of the same size as b. In other words, area A shall be of size N<NUM> × M<NUM>, wherein M<NUM> may or may not differ from N<NUM>, B shall be of size M<NUM> × N<NUM>, wherein M<NUM> may or may not differ from N<NUM>, and C shall be of size M<NUM> × M<NUM>, which may or may not differ from the block/CTU size N<NUM> × N<NUM>. Third, it is often desirable to, in an actual implementation, vary either N<NUM> and N<NUM> or M<NUM> and M<NUM>, or both of the sets at the same time. In fact, the preferred parameterization for the abovementioned IV-QPA embodiment uses fixed values M<NUM> = M<NUM> = <NUM> in units of luma-channel pixels, irrespective of N<NUM> or N<NUM> which, preferably, are varied input-adaptively by the image or video picture codec in dependence on said picture itself. For example, it is often beneficial to, in the encoder, use relatively large N<NUM> or N<NUM> for large input pictures (UHD or <NUM> or bigger, e. , N<NUM> = N<NUM> = <NUM>), and smaller values (e.g., N<NUM> = N<NUM> = <NUM>) otherwise.

<FIG> shows an apparatus <NUM> for varying or adapting a coding quantization parameter QP across a picture <NUM> in a style similar to <FIG>, i.e., by illustrating using dashed lines as to how this apparatus may be combined with an encoding stage <NUM> so as to result into a suitable encoder <NUM>. The apparatus <NUM> uses a predicted dispersion to determine the coding quantization parameter for a predetermined block as outlined above. The internal structure of apparatus <NUM> includes a dispersion determiner <NUM> followed by a QP determiner <NUM>. This time, however, the dispersion determiner <NUM> computes or determines a predicted dispersion. That is, dispersion determiner <NUM> determines a dispersion of a statistical sample value distribution of a predetermined block <NUM> or picture <NUM>, or a filtered version of this block <NUM>, but dispersion determiner <NUM> does not really exactly compute this dispersion but spatially or temporally predicts this dispersion from a spatial neighborhood or spatial temporal neighborhood of block <NUM>. To be even more precise, and as explained above, dispersion determiner <NUM> shifts a dispersion calculation actually performed from block <NUM> to a neighborhood of this block so as to obtain one or more actually computed dispersion values and a predicted quantization parameter for block <NUM> is determined based on this substitute which, in so far, represents a predictor of the block's <NUM> dispersion. For instance, dispersion determiner <NUM> actually performs dispersion computation for one or more spatially neighboring blocks <NUM>, spatially neighboring current block <NUM>,<NUM> of picture <NUM> and/or for one or more co-located blocks <NUM> of another picture. In <FIG>, for instance, a portion <NUM> of L-shape neighboring current block <NUM> has been used for the dispersion computation. It should be noted, however, that according to the embodiment of <FIG>, the dispersion computation not necessarily adheres to the examples set out with respect to <FIG>, i.e., the dispersion computation does not necessarily take place in the high-pass filtered domain.

The QP determiner <NUM> receives from dispersion determiner <NUM> the predicted dispersion and determines, based thereon, the quantization parameter for block <NUM>. Mainly details described above with respect to <FIG> and preceding embodiment may be used as applicable details for the embodiment of <FIG> individually or together. For instance, the dispersion determination performed by dispersion determiner <NUM> within portion <NUM> or <NUM> may use a Lp norm with p ≥ <NUM> to measure the dispersion, the dispersion measurement may be performed onto the high-pass filtered version of the respective portion or both, a high-pass filtered version and a low-pass filtered version thereof. As to high-pass filter and low-pass filter, the possibilities discussed above may apply. The same applies to possible variations as far as the measure of the dispersion is concerned. In this manner, apparatus <NUM> and determiners <NUM> and <NUM>, respectively act on a plurality of blocks picture <NUM> is composed of, thereby varying/adapting a quantization parameter across picture <NUM>.

When combined with encoding stage <NUM>, however, apparatus <NUM> may be connected into a prediction loop of encoding stage <NUM> or another interface of encoding stage <NUM> where a signal is available which corresponds to reconstructable version <NUM> of picture <NUM>, or video <NUM>, as available encoding order up to block <NUM>. Depending on the coding order underlying the encoding stage <NUM>, the reconstructable version <NUM> covers, for instance, a portion <NUM> of picture <NUM> substantially above and to the left of block <NUM>. Portion(s) <NUM> would lie within this portion. The reconstructable version <NUM> would also include, for instance, other pictures of video <NUM>, including block <NUM>. Thus, apparatus <NUM> would be combined with encoding stage <NUM> in a manner so that the dispersion determiner <NUM> would perform the predictive dispersion determination on the basis of the reconstructable version <NUM>. For instance, apparatus <NUM> would receive the information available for prediction stage <NUM>, i.e., at its input, as a reconstructable version <NUM> with the output of apparatus <NUM> at which the varied or adapted quantization parameter is output, being connected to the quantization parameter input of quantizer <NUM>. Naturally, the encoding stage <NUM> would still receive the original version of the signal to be coded, namely the video and/or picture <NUM> so as to encode same into the corresponding data stream <NUM>. In encoding, encoding stage <NUM> would use the quantization parameter as output for apparatus <NUM>.

Differing from <FIG>, however, no side information regarding the quantization parameter needs to be encoded into data stream <NUM>. As the predictive dispersion determiner <NUM> determines the predictive dispersion based on the reconstructable version <NUM>, the same quantization parameter, the same quantization parameter variation/adaptation may synchronously be performed on the basis of data stream <NUM> at the decoder side. Thus, in other words, in <FIG> it has been explained that apparatus <NUM> might be interactively combined by encoding stage <NUM> by receiving from encoding stage <NUM> some base quantization parameter which is determined by encoding stage <NUM>, for instance, according to some rate distortion optimization scheme is then varied/adapted by apparatus <NUM> in the manner described. In case of <FIG>, encoding stage <NUM> may also determine such base quantization parameter for picture <NUM> either as a whole or in slices, for instance, in picture <NUM>. This base quantization parameter may be encoded by encoding stage <NUM> into data stream <NUM>. Apparatus <NUM> also receives this base quantization parameter and varies same for each block <NUM> accordingly in the manner described. Additionally, however, apparatus <NUM> is also connected into the prediction loop of encoding stage <NUM> or, at least, receives from encoding stage <NUM> the reconstructable portion <NUM> of the reconstructable version <NUM> of picture <NUM> and based on the latter portion, namely within portion <NUM> and/or <NUM>, dispersion determiner <NUM> determines the dispersion for a current block <NUM>, i.e., by actually performing the dispersion determination spatially and/or temporally offset or shifted relative to current block <NUM> while then estimating or predicting the dispersion for block <NUM> based thereon.

With respect to remaining details, reference is made to the corresponding elements of <FIG> and <FIG>, respectively. That is, the encoding stage <NUM> may operate as described above with respect to <FIG> and <FIG>. Like in <FIG>, the encoding stage <NUM> may, however, also be of another coding concept type. As described above, the predictive dispersion determiner <NUM> may operate on a high-pass filtered version of block(s) <NUM> and/or <NUM> only, or on both high-filtered version and low-pass filtered versions thereof, or on an un-filtered version of the reconstructable version <NUM> within this block or these blocks. Further, different possibilities exist with respect to the number of actually determined dispersions for a current block <NUM>. For instance, as described with respect to <FIG> more than one such dispersion may be computer by dispersion determiner <NUM> such as, for instance, one per block of blocks <NUM>/<NUM>, within determining the coding quantization parameter QP for current block <NUM> based thereon. This may, as discussed with respect to <FIG>, enable a reduction of computation overhead by re-using some computed dispersion values for neighboring blocks for which the quantization parameter needs to be varied/adapted subsequently.

<FIG> shows, for sake of completeness, the apparatus <NUM> of <FIG> combined with a decoding stage <NUM> so as to result into a decoder <NUM> fitting to the encoder end of <NUM> in the sense that decoder <NUM> is able to decode from data stream <NUM> as generated by the encoder <NUM> of <FIG>, a reconstructed version of video <NUM> and/or picture <NUM>. The decoding stage <NUM> may, for instance, be construed as explained above with respect to <FIG>. Then, the QP output by apparatus <NUM> is received by the dequantizer <NUM>' with the apparatus <NUM> being fed with the signals input into prediction stage <NUM>'. As explained, data stream <NUM> does not need to carry any details or any side information concerning the quantization parameter variation/adaptation. Rather, apparatus <NUM> has access to the same information as on the side of the encoder <NUM> and accordingly, emulates the same operation and outputs, in a manner synchronous to <FIG>, a varied/adapted quantization parameter. Thus, again, and in order to be clear, differing from the previous description of <FIG> where the dequantizer <NUM>' of decoder <NUM> received the quantization parameter by explicit signaling in the data stream <NUM>, when the decoder <NUM> is used as a decoding stage <NUM>, then the dequantizer <NUM>' receives the quantization parameter by apparatus <NUM>.

Next, a possible extension of the above-described QP variation/adaptation concepts is described. Again, the description starts with a more concrete embodiment followed by a description of a broader embodiment with respect to <FIG> and afterwards, it is illustrated that this aspect may also be used irrespective of the other details set forth with respect to <FIG>.

Even with the QP adaptation described above, some image block b may be quantized too coarsely, preserving only the low-frequency average brightness (luma) and color (chroma) of b. To reduce this effect, a high-frequency SNR greater than zero dB can be enforced as follows. First, QP' is derived from the adapted qb via (<NUM>). Then, the mean value (DC offset) of all input luma pixels p ∈ b is calculated and subtracted from said p. The magnitudes of the resulting zero-mean luma pixels are averaged across b, yielding avg. Then, if avg < β·QP' (where empirical constant β depends on the luma image/video bit-depth), qb is reduced by a logarithmic difference: <MAT> with L(·) as given by (<NUM>). Using q'b, a modified QP' is derived via (<NUM>) and used for the actual coding. Note that, in practice, a small value of, e. , one is added to avg to prevent occurrences of L(<NUM>).

Also, an update of the rate-distortion parameter λ'b can be carried out similarly to (<NUM>), with ob therein now representing the logarithmic difference L(avg) - L(β·QP'). The block-wise non-zero high-frequency SNR enforcement described in this concluding section proved beneficial on some sports photography and video content, preserving a bit more of the images' fine-structure and texture on flat surfaces such as lawn (football), court (tennis), or race track (athletics).

<FIG> illustrates the just-outlined final check stage concept by illustrating an apparatus <NUM> for performing a final check onto a preliminarily determined final result for a quantization parameter for a certain block of a picture. In <FIG>, this quantization parameter is exemplarily indicated as QP<NUM>. At the output of apparatus <NUM>, the final version of the quantization parameter QP is output. Apparatus <NUM> may, for instance, be attached downstream apparatus <NUM> or apparatus <NUM> so as perform the final check onto the respective quantization parameter output by this apparatus <NUM> or <NUM>, but apparatus <NUM> may also be used irrespective of the afore-mentioned described figures and their embodiments as described later with respect to <FIG>.

The apparatus <NUM> comprises a comparator <NUM> and an adjuster <NUM>. The comparator <NUM> performs a comparison between the coding quantization parameter QP<NUM> assigned to a predetermined block of the picture and certain threshold, namely a threshold which depends on a mean difference of sample values of this predetermined block to the sample values' mean value. To this end, comparator <NUM> has, for instance, access to the original or un-quantized version of the predetermined block. In the above example, this threshold was AVG/β. In particular, the comparator <NUM> checks whether the coding quantization parameter QP<NUM> is greater or lower than the threshold and outputs the result to selector <NUM> of apparatus <NUM>. Selector <NUM> has two inputs, namely one receiving QP1, and another receiving QP2 as output by adjustor <NUM>. The adjustor <NUM> receives QP<NUM> and adjusts same to result into QP<NUM> with QP<NUM> corresponding to a finer quantization than QP<NUM>. If the first coding parameter deviates from the threshold towards a direction of coarser quantization, i.e., is greater than avg in the example set out above, selector <NUM> selects the input at which QP<NUM> is applied by adjuster <NUM> and outputs this quantization parameter QP<NUM> at its output as the quantization parameter QP to be finally used. Otherwise, selector <NUM> outputs QP<NUM> as QP. The adjustment by adjustor <NUM> may be performed as described above in equation <NUM>.

As already stated above at the beginning of the description of <FIG> and its corresponding concrete example, the comparison performed by comparator <NUM> may also advantageously be used if not using the quantization parameter variation/ adaptation according to any of <FIG> or <FIG>. To illustrate this, see <FIG> which shows an encoder <NUM> configured to encode picture <NUM> into data stream <NUM>. Encoder <NUM> is shown to comprise a comparator <NUM> which substantially corresponds to comparator <NUM> of <FIG>, and an encoding stage <NUM> which could be implemented in the manner described above with respect to encoding stages <NUM>. That is, the encoding stage <NUM> receives the signal to be coded, mainly picture <NUM> which, in turn, could be part of a video <NUM> with encoder <NUM> being a video encoder. Further, encoding stage <NUM> is of the lossy encoding type just as encoding stage <NUM> presented above was and for each of a plurality of blocks pictures <NUM> is composed of such as block <NUM>, the encoding stage <NUM> using a corresponding quantization parameter received by encoding stage <NUM> via a quantization parameter control input <NUM>. Additionally, encoding stage <NUM> is responsive to a comparison result forwarded by comparator <NUM>. In particular, comparator <NUM> receives the quantization parameter applied to encoding stage <NUM>, too and compares same with a threshold as described with respect to <FIG> with respect to comparator <NUM>. Many possibilities exist as to how the quantization parameter is applied via input <NUM> to encoding stage <NUM>. For example, the quantization parameter could be applied to encoding stage <NUM> at global scope, i.e., so that quantization parameter is constant across picture <NUM>. The quantization parameter applied at input <NUM>, and concurrently to comparator <NUM>, could alternatively vary across picture in slices for instance. Whatever scope, the quantization parameters applied to comparator <NUM> and encoding stage <NUM> could be set by default, or could be determined otherwise. <FIG>, for instance, illustrates that the quantization parameter is at least partially also controlled via encoding stage <NUM> by way of, for instance, a rate control of encoding stage <NUM>. Additionally, <FIG> illustrates the possibility that the encoder <NUM> comprises a QP adjuster <NUM> which adjusts or varies the quantization parameter across picture <NUM>. QP adjuster <NUM> could, for instance, be implemented in a manner coinciding with the description of apparatus <NUM> of <FIG>. That is, QP adjuster <NUM> may receive a base quantization parameter from encoding stage <NUM> at a scope of the overall picture <NUM> or slices thereof, and block-wise adjust the quantization parameter.

The block partitionings mentioned so far may be different. For instance, the quantization parameter entering comparator <NUM> and encoding stage <NUM>, for instance, may vary at a certain block partitioning or block granularity as just-described. That is, this QP may be defined globally for picture <NUM>, may vary in slices or may vary in predetermined blocks forming a partitioning of picture <NUM>. Comparator <NUM> also operates block-wise, but the blocks at which comparator <NUM> operates, may differ from the block partitioning underlying the definition of the quantization parameter entering comparator <NUM> and encoding stage <NUM>, respectively. As an example, the block partitioning may coincide. That is, the quantization parameter entering comparator <NUM> and encoding stage <NUM> may be defined at a block granularity coinciding with a block granularity at which comparator <NUM> performs the comparison.

Comparator <NUM>, then, compares for a certain block such as block <NUM> in <FIG>, the entering coding quantization parameter for this block <NUM> with a threshold which depends on a mean difference to sample average of this block <NUM>. This mean difference has been denoted as avg in the above description with a threshold being avg/β, but other examples may also hold true. Moreover, it should be noted the comparison not necessarily has to be performed in the non-logarithmic domain or, in other words, the coding quantization parameter may have another relationship the actual quantization step size or the quantization accuracy than the linear one with positive dependency as it has been true with QP denoted above. Frankly speaking, comparator <NUM> checks on the basis of the mean difference avg whether the quantization defined by the inbound coding quantization parameter for block <NUM> is fine enough or, in other words, whether the quantization step size defined by the inbound quantization parameter is below a predetermined factor times the mean difference where β is, for instance, smaller than <NUM>. The comparator forwards the comparison result to encoding stage <NUM> and the encoding stage <NUM> may, in addition to the functionalities associated with an encoding stage such as those discussed above with respect to encoding stage <NUM>, comprise the functionalities described in <FIG> with respect to blocks <NUM> and <NUM>. That is, encoding stage <NUM> may, depending on the comparison result, adjust for a corresponding block <NUM> the inbound quantization parameter so as to correspond to a finer quantization and use the thus adjusted coding quantization parameter within the respective block <NUM> for encoding instead of the originally inbound one, or may leave the inbound quantization parameter within the respective block as it is and use same for encoding within the respective block. As discussed above, the adjustment of the quantization parameter may, for instance, be made in such a manner that the adjusted quantization parameter is held to a value corresponding to the broadest quantization still complying with the mean difference. For instance, in adjusting the quantization parameter such as in block <NUM> or within encoding stage <NUM> the difference between the preliminary quantization parameter and the threshold is measured in logarithmic domain yielding the difference between the two L terms in equation <NUM>. This logarithmic measure for the difference is then applied to the preliminary quantization parameter in logarithmic domain, namely qb in case of equation <NUM>, in order to improve the quantization or get it finer which corresponds to a subtraction in case of <FIG>, i.e., qb is made smaller.

Naturally, the adjustment or reduction may also be performed differently such as by applying a certain factor or determine the amount of reduction by other means.

As already stated above, the encoding stage <NUM> then uses the adjusted quantization in case of adjustment, or the inbound quantization parameter in case of non-adjustment for encoding and with respect to details in this regard, reference is made to the discussion of previous <FIG>.

Turning to the third aspect of the present application, it should be noted that with respect to same <FIG> shows a schematic block diagram of an apparatus for varying a coding quantization parameter, firstly described in mono-channel sense and then serving as an example for a channel-specific QP adaptation apparatus, and a possible combination thereof with an encoding stage to yield an encoder, possibly a multi-channel encoder, the figure firstly ought to exemplify the possibility of using the dispersion of sample values of a high-pass filtered version of a current block so as to determine or adjust the quantization parameter, and then serving as an example for an QP adaptation apparatus for multi-channel coding. Fig. Likewise, <FIG> shows a schematic block diagram illustrating an apparatus for varying/adapting a coding quantization parameter across a picture, firstly described in mono-channel sense and then serving as an example for a channel-specific QP adaptation apparatus, and its possible combination with an encoding stage to yield a corresponding encoder, such as an multi-channel encoder, with the apparatus performing the quantization parameter variation/adaptation in a manner allowing synchronous performance of the same quantization parameter variation/adaptation at the decoder side, thereby avoiding spending any signaling overhead for explicitly signaling the quantization parameter variation/adaptation, and <FIG> shows a schematic diagram showing the apparatus of <FIG> and its combination with a decoding stage in order to yield a multi-channel decoder fitting to the encoder of <FIG>, i.e., being able to decode the data stream generated by an encoder of <FIG>, with the apparatus varying the quantization parameter across the picture synchronously with <FIG>.

As to the channels, more than two channels may be treated separately for QP adaptation in the just-described manner, such as for luma and two chroma channels or even four different color channels of another color space, or even other channel combinations.

The above described embodiments represent a deviation from contemporary perceptual image and video coding specifications which allow for the quantization parameter (QP) to be adapted, applied, and conveyed to the decoder on a picture-by-picture or block-by-block basis, in order to enable subjective optimizations of the coding quality. With color images and videos, this so-called QP adaptation can be performed separately and independently for one component (e.g., the luma/Y component in the YCbCr format) and for the remaining component(s) (e.g., the chroma/CbCr component in the YCbCr format). The High Efficiency Video Coding (HEVC) standard is a prominent recent example of where such separated luma/chroma QP adaptation is possible. However, a separated luma/chroma QP adaptation scheme has not been presented so far. In particular, the block-wise adapted QP values are determined equally for both the luma and chroma component of the image/video. According to above embodiments, QP adaptation is separately and independently performed on, for example, luma and on the remaining component(s) when coding a multi-component image or video. Furthermore, QP adaptation may, separately and independently, be applied on each and every component of the multi-component image or video. Existing or currently developed image or video coding specifications such as HEVC or its successors may be extended, to allow adaptation, application, and signaling of QP data separately and independently for each and every component of a multi-component image or video, in order to allow to achieve maximum visual improvement of coding quality.

The inventive data stream can be stored on a digital storage medium or can be transmitted on a transmission medium such as a wireless transmission medium or a wired transmission medium such as the Internet.

Claim 1:
Apparatus for varying a coding quantization parameter across a picture, configured to
determine a dispersion of a statistical sample value distribution of a high-pass filtered version of a predetermined block of a picture, and
determine a coding quantization parameter for the predetermined block depending on the dispersion,
characterized in that
the apparatus is configured to, in determining the dispersion, use an Lp norm with p≥<NUM> to measure the dispersion, and
wherein the apparatus is configured to, in determining the coding quantization parameter, subject the dispersion to logarithmization,
wherein the apparatus is configured to
determine a further dispersion of a statistical sample value distribution of a low-pass filtered version of the predetermined block, which is DC compensated, and
perform the determining of the coding quantization parameter for the predetermined block further depending on the further dispersion by computing <MAT>
where ob is a QP index for the predetermined block b, a = ¼, L(·) is a logarithmic conversion, Ṕb is the dispersion of the statistical sample value distribution of the high-pass filtered version of the predetermined block, Ṕb is the dispersion of the statistical sample value distribution of the low-pass filtered version of the predetermined block, avg(Ṕ<NUM>)) is an average of the square the dispersion of the statistical sample value distribution of the high-pass filtered version across the picture in entirety, and avg(Ṕ<NUM>)) is an average of the square the dispersion of the statistical sample value distribution of the loa-pass filtered version across the picture in entirety.