Encoding data represented as a multi-dimensional array

Abstract: A method and apparatus for encoding interframe error data in an image transmission system, and in particular in a motion compensated image transmission system for transmitting a sequence of image frames from a transmitter to a receiver, employ hierarchical vector quantization and arithmetic coding to increase the data compression of the images being transmitted. The method and apparatus decimate an interframe predicted image data and an uncoded current image data, and apply hierarchical vector quantization encoding to the resulting pyramid data structures. Lossy coding is applied on a level-by-level basis for generating the encoded data representation of the image difference between the predicted image data and the uncoded original image. The method and apparatus are applicable to systems transmitting a sequence of image frames both with and without motion compensation. The method and apparatus feature blurring those blocks of the predicted image data which fail to adequately represent the current image at a pyramid structural level and shifting block boundaries to increase the efficiency of the vector quantization coding mechanism. The method further features techniques when gain/shape vector quantization is employed for decreasing the data which must be sent to the receiver by varying the size of the shape code book as a function of the gain associated with the shape. Thresholding and the deletion of isolated blocks of data also decrease transmission requirements without objectionable loss of image quality.

Description: This application is a divisional application derived from Application No. 88905043.1 entitled "A Hierarchical Encoding Method and Apparatus for Efficiently Communicating Image Sequences". The invention relates generally to data communication and signal processing methods and apparatus, and in particular to a method and apparatus for reliably and efficiently encoding and decoding sequences of image data, for example, that are transmitted over a telephone communications channel. The transmission of sequences of images, and in particular sequences of naturally occurring images such as those represented by a television signal, has been the subject of a significant amount of investigation. Typically, investigators have relied upon the highly redundant nature of successive images in the sequence and have often modeled the image data as a Markov process with a correlation coefficient close to unity. The three-dimensional Markov model provides a motivation for utilizing differential pulse-code-modulation (DPCM) and transform coding techniques to take account of the interframe redundancy. By analyzing the nature of typical moving video, it is easy to become convinced that the principal change occurring between successive frames is the inhomogeneous motion of the objects within the frame. It has also been recognized that an accurate apparatus and method of estimating and compensating for this spatially dependent motion enables the construction of an interframe data compression method and apparatus which can have substantially better performance than can be achieved by sending a signal representative merely of the difference between successive frames. As a result, various motion compensating coding methods and apparatus have been developed. These systems typically are either receiver-based motion compensation systems or transmitter-based motion compensation systems. In the receiver-based motion compensation system, the receiver makes a prediction as to the motion and compensates the previous frame for the expected motion. The transmitter, operating in the same manner, then sends only an error signal describing what must be done at the receiver in order to correct the receiver predicted frame. The error signal is typically coded to reduce its bandwidth. For a transmitter-based motion compensation system, the motion estimation process occurs only at the transmitter. Displacement vectors are generally determined over various regions of the image and this data is then transmitted to the receiver along with an error information data signal. At the receiver, the compensation process is performed on the previously coded image first using the motion information provided by the transmitter. The error signal data provided by the transmitter is then added to the thus compensated receiver image in order to maintain picture quality. There is thus typically provided for a transmitter-based motion compensation system a plurality of displacement vectors, and in at least one preferred embodiment, each vector is associated with a specific region or block of the image. The blocks are typically non-overlapping and have, for example, a size of eight picture elements (pixels) by eight picture elements. Various methods have been employed for encoding the motion compensation data associated with each of the blocks. Hinman, in his co-pending application U.S. Serial No. 740,898, filed June 3, 1985, now US-A-4,703,350, describes a lossy coding method for encoding the motion-compensation displacement information. Many methods have also been employed for encoding the error information data signal in a transmitter-based motion compensation system. In the above-identified Hinman application, a lossy compression method and apparatus are disclosed. While these methods are highly advantageous, and provide excellent results, it is nevertheless desirable to further improve the compression of the data information and thereby enable high quality image reproduction using still less channel bandwidth. It is further desirable to provide better control over the data transmission by controlling, for example, the bit rate associated with the image. Often, during a scene change, for example, there exists substantial information to be transmitted, so that during a single frame time, insufficient bandwidth is available to transmit all of the information. Accordingly, various methods have been implemented to selectively limit the number of bits of information transmitted over the channel. One of these methods, described in Ericsson, U.S. Serial No. 001,326, filed January 7, 1987, now US-A-4816914 entitled "A Method and Apparatus for Efficiently Coding and Decoding Image Sequences," employs quad-tree coding in connection with the transmission of portions of a transform coefficient data set. The quad-tree coding advantageously provides a more graceful degradation of the image during heavy motion or scene changes. In Signal Processing, vol. 11, 1986, pages 387 to 404, an article by Bierling et al entitled "Motion Compensating Field Interpolation Using a Hierarchically Structured Displacement Estimator" there is disclosed a motion compensation system using quantized data values which represent a digital television sequence. A hierarchically structured displacement estimator provides a displacement vector with interframe components for each picture element of the transmitted fields to be interpolated. An article entitled "Hierarchical encoding of image sequences using multistage vector quantization" by B. Hammer et al in "ICASSP 87, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Dallas, Texas, US", purporting to relate to a presentation made in April 1987, refers to vector quantization as an encoding technique for low data rate image transmission, and to multistage vector quantization in combination with a block-overlapping pyramid transform to allow quantization of large blocks in a hierarchical manner for transmission of picture phase sequences. US-A-4661849 (Hinman) discloses an image sequence transmission method for transmitting a sequence of successive images over a bandwidth limited channel. The transmitter has an motion estimator for estimating the motion displacement between successive image frames of the sequence, the estimator dividing each image into non-overlapping blocks each including a plurality of picture elements. Initial values of motion vector displacements are selected and, in an iterative process, successive values of the motion displacement vector for each block are determined. The iteration process is terminated when an iteration error associated with a steepest descent method is less than a threshold value. It is an object of the present invention to provide an improved method of encoding image data. According to the invention, a method for encoding data values for representing image data in an image transmission system, represented as a multi-dimensional array of data values, comprises the steps of: quantizing the data values, deleting all quantized data values having a zero value for each of its nearest neighbors, and applying vector quantization coding to the remaining data values. The array may be a two dimensional array with eight nearest neighbors, and the method may include the step of motion compensating the image transmission system for transmitting a sequence of images over a communications path. The description which follows also includes methods of encoding interframe error data in an image transmission system, particularly in a motion compensation image transmission system, for transmitting a sequence of image frames from a transmitter station to a receiver station. An interframe predicted image data representing a prediction of the current image frame is decimated for generating a prediction pyramid data structure representing the current image prediction and a having a plurality of decimation levels. This can be followed by decimating an uncoded current image data representing the current uncoded image frame for generating a current image pyramid data structure representing the current image and having the plurality of decimation levels, and applying a hierarchical vector quantization encoding method to the prediction and current image pyramid data structures, on a level by level basis, for generating an encoded data representation of the difference between the predicted image data and the uncoded current image data. The method may be applied to motion compensation image transmission, with image frames being transmitted from a transmitter station to a receiver station. Also described are the steps of applying the hierarchical encoding method to the data structures of a level on a block-by-block basis and blurring blocks of the predicted image representation when a predicated image data fails to adequately represent that block portion of the original image, and shifting block location boundaries from frame to frame of the sequence of image frames for improving the encoding efficiency. The description includes the step of employing arithmetic coding for generating, in part, the encoded representation. The following description sets out the steps of applying lossy compression hierarchical encoding to the prediction and current image data structures on a level-by-level basis for generating the encoded data representation of the difference between the predicted image data and the uncoded current image data. The applying step features the step of interpolating, for at least one lower level, the image data from a higher level. Also described are the steps of forming a difference image representing, on a pixel-by-pixel basis, the difference between a predicted image data for a current image frame and an uncoded current image data representing the uncoded current image frame, decimating the difference image for generating a difference image pyramid data structure having a plurality of decimation levels and applying hierarchical vector quantization encoding to the difference image pyramid data structure on a level-by-level basis for generating an encoded data representation of the difference between the predicted image data and the uncoded current image data. This may include forming the predicted image data using interframe motion compensation. Gain/shape vector quantization may be applied to blocks of the array of data values for encoding the values, coupled with varying the size of a shape code book for the vector quantization as a function of the gain associated with the shape. The detailed description covers circuitry for decimating the interframe predicted image data for a current image frame for generating the prediction pyramid data structure having a plurality of decimation levels, circuitry for decimating the uncoded current image data representing the current uncoded image frame for generating a current image pyramid data structure having the plurality of decimation levels, and circuitry for applying hierarchical vector quantization encoding to the prediction and current image pyramid data structures on a level-by-level basis for generating an encoded data representation of the difference between the predicted image data and the encoded current image data. Also disclosed are circuitry for applying the hierarchical encoding method to the data structures of a level on a block-by-block basis, circuitry for blurring blocks of the predicted image representation when a predicted image data fails to adequately represent that block portion of the original image, circuitry employing artithmetic coding for generating, at least in part, the encoded representation, and circuitry for shifting block boundary locations from image to image in the sequence of image frames for improving the encoding efficiency. The described apparatus further features circuitry for applying lossy compression hierarchical encoding to the prediction and current image pyramid data structures on a level-by-level basis for generating the encoded data representation of the difference between the predicted image data and the encoded current image data. The applying circuitry features elements for interpolating, for at least one lower level, the image data from a higher level. In yet another aspect of the description, the apparatus for encoding the interframe error data in an image transmission system for transmitting a sequence of image frames features circuitry for forming a difference image representing, on a pixel-by-pixel basis, the difference between predicted image data for a current image frame and an uncoded current image data representing an uncoded image frame. Decimation circuitry is provided for decimating the difference image; for generating a difference image pyramid data structure having a plurality of decimation levels; and for applying a hierarchical vector quantization encoding to the difference image pyramid data structure on a level-by-level basis for generating an encoded data representation of the difference between the predicted image data and the encoded current image data. In the described system the number of bits employed to transmit each image of a sequence of images is controlled while providing for graceful degradation of the image during a scene change or during periods of heavy motion. The system can reliably transmit and receive an accurate estimate of the displacement of the pixels of a scanned image in a sequence. Improved motion estimation can be achieved in an encoding and decoding method and apparatus which enable real-time, accurate determination of the regional displacement in an image transmission device. The invention will now be described by way of example with reference to the drawings in which: Figure 1 is an electrical block diagram of a image communications system; Figure 2 is an electrical block diagram of the transmitter of a motion-compensated image coding apparatus; Figure 3 is an electrical block diagram of the receiver of a motion-compensated image encoding system for receiving the channel signals for the transmitter of Figure 2; Figure 4 is an electrical block diagram of a motion-compensation apparatus for a field of under sampled motion vectors; Figure 5 is a diagrammatic representation of a spatial interpolation process; Figure 6 is an electrical block diagram of an iterative spatial-domain motion estimation apparatus utilizing adaptive, steepest descent error minimization; Figure 7 is an electrical block diagram of an iterative spatial-domain motion estimation apparatus utilizing adaptive, steepest descent error minimization with an improved data processing structure; Figure 8 is a diagrammatic presentation of the relative locations of adjacent blocks used in predicting an initial displacement motion vector value; Figure 9 is a block diagram of the lossy compressor 28 of Figure 2; Figure 10 is a block diagram of the lossy compressor 46 of Figure 2; Figure 11 is a diagrammatic representation of a one dimensional decimation process; Figure 12 is a detailed electrical block diagram of the lossy compressor 46; Figure 13 is an electrical block diagram of the transmitter of a motion-compensated image coding apparatus having adaptive filtering and employing the invention; Figure 14 is an electrical block diagram of the receiver of a motion-compensated encoding system for receiving the channel signals from the transmitter of Figure 13; and Figure 15 is a general block diagram of an alternate embodiment of the lossy compressor. Referring to Figure 1, a communications system 6 has a transmitter 8 which, in accordance with a preferred embodiment of the invention, has a camera 10 for providing a video signal to an analog-to-digital converter and frame buffer 12. The frame buffer portion of the analog-to-digital converter and frame buffer 12 is capable of storing a full frame of the video, sampled to, for example, eight bits across a 256x240 pixel raster. The entire coding and motion compensation process takes place in the digital domain. The transmitter has an error signal circuitry 14 and a motion estimation and coding circuitry 16. A channel encoder 18 channel encodes the outputs of the error circuitry 14 and motion estimation and coding circuitry 16 and passes the thus encoded data onto a channel 20 for transmission to a receiver 21. The illustrated motion estimation and coding circuitry 16 of Figure 1, in accordance with a preferred embodiment of the invention, and referring to Figure 2, compares a present original input frame image, available over lines 22, with the previous original input image, available in this illustrated embodiment from a frame buffer 24. A motion estimator circuitry 26 generates a measure of the motion displacement between the frames input thereto, and can be any of a number of motion estimation devices as are well known in the art. In a preferred embodiment to be described hereinafter, the motion estimation device 26 uses an adaptive steepest descent error minimization method to generate the motion displacement measures as described in Hinman, U.S. patent US-A-4,661,849. The output of the motion estimator 26 is a field of motion vectors which, as noted above, provide a measure of the motion displacement between input frames. This vector field provides a description of how to map a previous input frame or input image from buffer 24 into the best approximation of the present input frame or image over lines 22. By "best" is meant an error metric such as, for example, a mean-squared-error error measure. Typically, and in the illustrated embodiment, the motion estimator 26 uses a region matching technique between non-overlapping blocks of the previous and present input images. Should motion occur for a region in the present image, the estimator will determine which block in the previous image is the best match for the block in the previous image, and the value of the displacement is the difference between a new coordinate pair for the block in the present image and the original coordinate pair for the block in the earlier image. That determination defines the motion vector to be associated with the block in the present image. Since scenes are generally composed of several large objects moving uniformly over time, there is a high degree of correlation in the motion vector field. To avoid transmitting redundant information, and to reduce the data bit requirements, the preferred embodiment of the invention modifies the motion vector field, thereby losing some information, to facilitate the compression of the motion representing data. In the illustrated embodiment, this operation is represented by a "lossy compressor" 28 which reduces the amount of data, and hence the bandwidth, required to represent the motion vector field. Noting the similarity between motion vector field and natural images, predictive, transform, or interpolative coding of the two independent components of the vector field can be employed by the lossy compressor 28. Thus the lossy compressor circuitry 28 is employed for coding the motion vector field available over lines 32, and provides, over lines 30, a coded motion signal representative of the motion vectors. This output of the lossy compressor 28, as noted above, will not, upon decoding, exactly reproduce the signals over lines 32 (which provide the measure of motion displacement) and, therefore, have some error signal associated with them. Nevertheless, the reduction in the data requirements of a lossy compressor 28, when compared to, for example, a PCM exact coding method, are so substantial, that the use of a lossy compressor, is a significant advance in the art. One preferred lossy compression circuitry employs a discrete cosine transform and the circuitry incorporates a processing method described in co-pending application, U.S. Serial No. 740,806, now US-A-4,754,492 entitled "Method and System for Adapting a Digitized Signal processing System for Block Processing With Minimal Blocking Artifacts" and filed on June 3, 1985. The inventor is Henrique Malvar. The lossy compressor circuitry 28, in the illustrated embodiment of the invention, provides for block transformation and includes additional circuitry for reducing the number of bits (the bandwidth) required to describe the transformed motion vector field. The lossy compressor 28 can thus provide for varying the quantization step size (and, if necessary, the threshold) with which the transform coefficients which define the motion vector field are "digitized," thereby reducing the number of output bits as either the quantization step size or the threshold (or both) increase in value. The lossy compressor 28 also preferably employs arithmetic coding which is applied to the transform coefficients modeled as a Markov Process. This encoding method provides a substantial reduction in output bits, over, for example, the output of the system described in US-A-4,703,350. The output of the lossy compressor circuitry 28 over lines 30, as noted above, is passed to the encoder 18. In addition, those signals are employed by the error circuitry 14 for determining what the receiver would have seen, absent any errors in the channel, and thereby providing the mechanism for determining the prediction error signal, that is, the signal representing the difference between what the receiver 21 would have predicted based upon the coded motion signal representation over lines 30, and the true image input. The output of the lossy compressor 28 over lines 30 is used by a reconstructor circuitry 34 for producing, at its output, a signal representative of the measure of motion displacement, the motion vectors, on lines 32. The difference between the signals over lines 36, the output of the reconstruction circuitry 34, and the signals over lines 32, represents the coding error introduced by the lossy compression apparatus 28. The output of the reconstruction apparatus 34, over lines 36, is directed to a motion field interpolation circuitry 38 which operates in the spatial domain to associate with each picture element a motion displacement vector. Thus, while the input signals over lines 36 represent motion displacements for groups or regions of elements, for example, the picture elements of a 4 x 4 block, the motion field interpolator 38, as described in more detail below, resolves that data so that there is associated with each picture element, a motion displacement vector. The resulting output of the motion field interpolator 38, over lines 40, is designated the motion reconstruction signal. The motion reconstruction signal is applied to a motion compensation apparatus 42 which forms part of an error reconstruction loop 43. The error reconstruction loop 43 includes a frame buffer 44, a lossy compression circuitry 46, and a reconstruction circuitry 48. The inputs to the lossy compression circuitry 46, over lines 22 and 51 respectively, are the original input image for the current frame and the estimated receiver signal, that is, the signal which, absent any further data, the receiver 21 will reconstruct and display. The lossy compressor 46 provides the receiver with further encoded data, the error reconstruction signal, for reducing, and in principle eliminating, the difference between the original input image and the estimated receiver signal. That difference is coded to reduce its bandwidth and the resulting signal, the error reconstruction signal over line 52, is delivered to the channel encoder 18. The lossy compressor 46 in the above referenced Ericsson patent application is a two-dimensional block encoder which employs a quantizer having a uniform quantization step size; and the output of the block transform can be advantageously further reduced in bandwidth and encoded according to the processes described above in connection with the lossy compressor 28. However, in the preferred and illustrated embodiment of the invention a hierarchical vector quantization encoding method and apparatus are advantageously employed in implementing the lossy compressor 46. The error reconstruction signal is also sent to the reconstruction apparatus 48 which provides an operation which is the inverse to that imposed by the lossy compressor 46. There results, therefore, at the output of the reconstruction apparatus 48, an error reconstruction image over lines 54. The error reconstruction image is added to the expected output of the motion compensator, (which is the estimated receiver image over lines 51) and the resulting signal, an estimated previous receiver image (the predicted receiver image for the previous frame), is stored in the frame buffer 44. As noted above, the input to the frame buffer 44 is the estimated previous receiver image. This receiver image, which takes into account all data received by the receiver, corresponds to the reconstructed receiver image for a frame. The image output from the frame buffer 44 over lines 64 is the image which the motion compensation circuitry 42 modifies in accordance with the output of the motion field interpolator 38 over lines 40. The output of motion compensator 42 thus represents the predicted receiver image as a result of reconstructing the output data from lossy compressor 28. At the receiver 21, referring to Figure 3, the data from the channel is decoded by a channel decoder circuitry 70 and the resulting receiver error reconstruction signal over lines 72 and receiver coded motion signal representation over lines 74 are delivered to reconstruction circuitry 76, motion compensator 99, and reconstruction circuitry 78 respectively. The reconstruction circuitries 76 and 78 each provide for decoding the codes employed by the transmitter 8 to effect the operations performed by reconstruction circuitries 48 and 34, respectively, of the transmitter, as described in more detail hereinafter. The output of the error reconstruction circuitry 76 is delivered to a recovery loop 80 in which motion compensating signals over lines 82 are added to the error image representation over lines 84 to produce a reconstructed receiver signal over lines 86. That signal is delivered to a digital-to-analog circuitry 90 and from there to a monitor 92 for viewing. Motion reconstruction signals are generated by a motion field interpolator 96 corresponding to the motion field interpolator 38 of the Figure 2. The motion field interpolator 38, as noted above, provides a motion vector for each picture element of the image and hence allows the frame interpolator to accurately predict what the image would have been at any selected time between received frames. The reconstructed receiver images over lines 86 are successively stored in a frame buffer 98 and are delivered to a motion compensator 99 which also receives signals from the motion field interpolator 96. The output of the motion compensator 42, representing the expected receiver image in the absence of an error correction, corresponds to the signal over lines 51 in the transmitter 8, and is delivered to the adder 100 for combination with the output of the error reconstruction circuitry 76 over lines 84. The transmitter and receiver circuitries 8, 12 of Figures 2 and 3 can be modified in a number of ways as described, for example, in US-A-4,703,350 and US-A-4,816,914 referred to above. While these alternate embodiments of transmitter and receiver structure are applicable in different communications configurations, the invention described and claimed herein relating to a hierarchical coding system is not dependent upon which of those particular transmitter configurations is employed and will therefore be described solely in connection with the typical transmitter and receiver configuration set forth hereinabove. The Motion Field Interpolator (38, 96) Referring to Figure 4, the motion field interpolator 38 receives from the reconstruction circuitry 34, a motion displacement vector over lines 36 for each block region of the image. For example, for a color television video signal, a typical luminance image can have a block size of 8x8 pixels while a typical chrominance image can have a block size of 4x4 pixels. The motion field interpolator 38, employing a selected interpolation method, then associates with each pixel of the frame, an interpolated motion vector displacement value. In accordance with the preferred aspect of the invention, a raised cosine interpolation function is employed for associating with each pixel a displacement value. The interpolation function is stored at 130. The input vector field is stored in a buffer 132 and has a low resolution corresponding to the block size. Thus, in accordance with this aspect of the invention, each displacement vector from reconstruction circuitry 34 is associated with the center of a multi-pixel region. Thus, for a 4x4 block region, referring to Figure 5, the interpolation vectors are associated with a center position, that is, positions 400, 402, 404 which are not, for a 4x4 block, associated with any one picture element. The interpolation process, performed by a vector interpolator 134 (Figure 4) operates in both the X and Y directions. Thus, the displacement vector associated with the 4x4 pixel block region centered at 400 and the corresponding displacement vector associated with the region centered at 402, for example, can be interpolated with respect to the X direction, while the displacement vectors at regions centered at 400 and at 404 can be employed with respect to a Y interpolation. In general, the interpolation process employs a plurality of displacement vectors surrounding a point of interest for deriving the value of the displacement vector at the point. Thus, an X and Y interpolated displacement vector value is assigned by the vector interpolator 134 in accordance with the interpolation function being used for each pixel of the image. In other embodiments of the invention, interpolation functions other than the raised cosine can be employed. For example, a linear interpolation function, or a trapezoidal shaped interpolation function can be employed, the latter for reducing the computational load. The output of the transmitter motion field interpolator 38, or the receiver motion field interpolator 96 (which operates in a manner identical to that of interpolator 38), is directed to the full motion compensation circuitry 42 in the transmitter 8 and to the full motion compensation circuitry 80 in the receiver 21. The full motion compensation circuits 42 and 80, using incoming frame image data from frame buffers 44 and 98 respectively and the motion field interpolator output data, effect, in the transmitter, generation of the estimated receiver image over lines 51, and in the receiver, the received estimated image over lines 82. The motion compensation circuitry 42, 80 maps each output pixel location to a location in the previous frame as indicated by the displacement vector value associated with that output pixel location. The displacement vectors are specified by the motion field interpolation circuitry associated therewith. In particular, referring to Figure 4, this is the output of vector interpolator 134. There results, however, for some coordinate locations of the new image field, a mapping from pixel coordinates in the previous frame which do not fall upon a grid location. That is, the interpolated motion displacement vector may call for a movement of, for example, 1 1/4 picture elements. In these instances, the motion compensation apparatus 42 employs a spatial (or pixel) interpolation, for example a linear spatial interpolation of the 2x2 block of pixels surrounding the noninteger location, for determining a pixel value from the previous frame. Other interpolation functions could, of course, be employed, for example, the value selected for the noninteger coordinate of the previous frame can be the value of the pixel closest thereto. Alternately, a raised cosine interpolation function can be employed. The motion field interpolator 38 and motion compensator 42 can be implemented in hardware, in software, or in a combination of hardware and software. The Lossy Compressor (28) In accordance with a preferred embodiment of the invention, the lossy compression circuitry 28 employs a block transform encoding method for coding the motion estimation output signal. The output of the motion estimation circuitry 26 has the appearance, in essence, of a highly correlated image wherein each picture element represents not a portion of a visual image but, rather, a displacement value. In the illustrated embodiment of the invention, the lossy compression circuitry 28 employs a discrete cosine transform. Circuitry 28, then, for example, operates on the displacement vector output of the motion estimation circuitry 26 to provide coefficient data which is then adaptively subjected to a threshold and uniform quantization process. In this circumstance, the reconstruction circuitry 34 then employs the inverse discrete cosine transform as is well known in the art. In yet another aspect of the invention, and as described the above-noted US-A-4,754,492, preprocessing techniques can be employed for improving even more upon the transform method described hereinabove, to substantially eliminate the block coding artifacts. In still another embodiment of the invention, the lossy compressor 28 can be implemented using a short-space Fourier transform, such as that described in U.S. Application Serial No. 713,478, filed on March 19, 1985 (US-A-4703349) for a Method and Apparatus for Multi-Dimensional Signal Processing Using a Short-Space Fourier Transform, and assigned to the assignee of the present invention. The lossy compression circuitry 28 contains data bandwidth compression elements for controlling and reducing the bit rate output applied and directed to the channel encoder 18. Referring to Figure 9, in accordance with the preferred embodiment of the invention, and examining the lossy compressor 28 in detail, the block transformation 450 to which the input to the lossy compressor 28 is subjected, provides that each block in a spatial domain be transformed into an array of transform coefficients (some or all of which may be zero). Those coefficients are then quantized, and if necessary subjected to a thresholding process to further reduce the number of non-zero coefficients. In accordance with the invention, an increased threshold value and/or an increased quantization step size, reduces the number of non-zero coefficients to be coded and further reduces the length of the code words required to describe the coefficients output by the block transform method. In accordance with the preferred embodiment of the invention, the quantization step size for a frame is advantageously predicted prior to the encoding of the frame. A quantization prediction and control 452 is employed by the lossy compressor 28, in response to the energy in the motion signals as provided from motion estimator 26 over lines 188. Using the predicted quantization step size, the lossy compressor 28 encodes, at 454, the remaining block transform coefficients using, for example, an arithmetic coding technique. This technique, known in the facsimile art, is implemented to efficiently code the locations of the non-zero coefficients. The apparatus variable length codes at 456, again using the arithmetic coding technique, the quantized non-zero array coefficient values to be transmitted, and provides the variable length code data to the channel encoder 18. (The lossy compressor 28 then provides the quantizer encoded data to the reconstructor 34 and all arithmetic encoded data only to the channel encoder.) In operation, the coefficients of each transformed block selected to be updated are quantized using the predicted quantization step size, subject to initial thresholding; and thereafter, the coefficient array locations are coded. The compression process thus consists of several operations: quantization, reconstruction, code word generation, and bit stream generation. The quantization, reconstruction, and code word generation are, in the illustrated embodiment, performed together. For each transform coefficient associated with a block, the coefficient value is, as noted above, subjected to a threshold cutoff value and then quantization. The quantizer employed herein is a uniform quantizer, and the threshold and quantizer step size can be determined as noted above. A typical threshold is 1.5 times the quantization step size and the expected peak to peak value of the signal to be quantized is, in the illustrated embodiment, divided into 256 equal steps. Each transform coefficient is first compared to the threshold value. If the value of the coefficient is greater than the threshold value (either positive or negative), then the coefficient is quantized and coded. If the value is below the threshold value, then the coefficient is set to zero and is not coded. For the coefficients which are quantized, the value of the coefficient is multiplied by the inverse step size. If the resulting quantization value is, in the illustrated embodiment, greater than eight bits, the coefficient value is cut off to be the Largest allowable eight bit value (+127 or -128 in the illustrated embodiment). This value is then used as an input for arithmetic encoding at the transmitter for deriving the transmitter variable length code word. The eight bit code word value is also used at the transmitter 8 to reconstruct the transform coefficient. The quantized coefficient value is multiplied by the step size and will be made available to the associated reconstructor for each transmitted block. In the illustrated embodiment, the same threshold and quantizer step size is used for all coefficients associated with an image frame. In addition, probability estimates are used for all coefficients of a frame. The quantization of each transform coefficient is performed at 454 as part of the overall coding process. The code words identify the transform array location to which each of the transmitted amplitude code words corresponds. As noted above, the lossy compressor 28 provides for limiting the number of bits in each frame to a constant level. In view of the use of a variable length code, as described hereinafter, it is not possible to exactly predict the number of generated bits and the problem thus is not "trivial." The traditional approach of collecting the bit stream in a buffer and preventing overflow or underflow of the buffer by a feedback configuration has associated therewith a disadvantageously long buffer delay time. In accordance with the preferred embodiment of the invention, the predetermined number of bits is approximated by predicting the quantizer step size dependent upon the motion frame energy. The prediction of quantization step size, the encoding, and the decoding, can be implemented in hardware, in software, or in a combination of the two. The Lossy Compressor (46) As noted above, the lossy compressor 46 receives as inputs the original uncoded signal over line 22 and signals representing the estimated receiver image over lines 51. The lossy compresscr 46 uses those signals for encoding the difference between them, and outputs the encoded error reconstruction signal over lines 52. This signal corrects for most errors not properly compensated for by the motion compensation system. In the preferred embodiment of the invention a hierarchical vector quantizer coding method and apparatus is employed; however, in other embodiments other hierarchical methods employing a decimated pyramid structure and interpolation, as described below, can be employed. Referring now to Figure 10, the estimated receiver image over line 51 (often referred to as the "warped" image) and the original uncoded image over lines 22 are decimated (that is, filtered and subsampled as described below) by decimation circuitries 502, 504, respectively, four times. At each decimation stage, the image is subsampled by a factor of two both horizontally and vertically. Thus, five levels of images for the luminance image are available at resolutions of, in the illustrated embodiment, 256x240, 128x120, 64x60, 32x30, and 16x15 picture elements for the luminance. The set of images, at the different image resolutions, is commonly referred to as a "resolution pyramid." The base of the pyramid is the full resolution image while the top of the pyramid is, in the illustrated embodiment, the 16x15 pixel image. Similar resolution pyramids are formed for the "I" and "Q" chrominance components of a color image. However, for the discussion below, only the luminance component of the image shall be discussed. The same apparatus and processing steps are equally applicable to the chrominance components of the image. In accordance with the hierarchical system, encoding of the image diference between the warped image and the original uncoded image is performed by an encoding circuitry 506 on a level by level basis, from the top level to the bottom level of the resolution pyramids. The process terminates at that resolution when no additional bits are available for video transmission. Thus, during a moderate motion the system will typically reach the bottom or base level of 256x240 pixels while during a heavy motion the encoding may stop at the 128x120 level. Typically, during a scene change, the apparatus will run out of transmission bits earlier in the pyramid. Thus, in general, large changes of image or scenes are typically described first at the higher levels with the details being filled in in later frames. More particularly, in accordance with a preferred hierarchical coding system using vector quantization, encoding begins at the top level, that is, the 16x15 image. The 16x15 version of the warped image is used as the prediction. Recall that this corresponds to the image (decimated) that is created at the receiver absent any additional information. This top level prediction is subtracted from the 16x15 decimated top level image of the original image. The difference image, representing the error at that top level, is quantized and the quantized information is directed to the encoder 18 for transmission to the receiver. Thereafter, the quantized difference image is added to the prediction image, at the 16x15 level, to form a 16x15 reconstructed image which the receiver will also create. At the lower levels, the prediction version of the image is formed in a different fashion. In accordance with the invention, the prediction is derived from the higher level reconstructed image and from the current level warped image as follows. First, an interpolation error image is derived by interpolating the higher level warped image and subtracting it from the current level warped image. The resulting warped interpolation error image thus essentially extracts the spatially higher frequencies of the warped image, that is, information not present in the higher level image. The higher level reconstructed image is then interpolated to form an interpolated, reconstruction image at the current level. Finally, the warped interpolation error image is adaptively added to the interpolated reconstruction image to generate the prediction image. However, as described below, the warped interpolation error image is used where it improves the prediction but not otherwise. This is decided on a block-by-block basis, and the decisions are transmitted to the receiver as "side" information. Thereafter, the steps for generating the difference signal at this lower level are the same as those at the top level, that is, the current level prediction image is subtracted from the current level original image and that difference is quantized and transmitted to the receiver. Thereafter the quantized difference is added to the prediction image at that level to form a new reconstruction image. This procedure is repeated through the resolution pyramid until the bottom level is reached. The reconstructed image at the bottom level is the output image at the level, and it is that image that is displayed by the decoder. That image is also used as described above to form a warped image for the next frame. The warped image reconstruction at the transmitter is, as noted above, performed by the reconstruction circuity 48. If all of the available bits have been used before the bottom level is reached, the predictions at the lower levels are still generated in the same manner; however, no coding, that is, no quantized difference information is sent to the receiver. Instead, the prediction at the lowest levels will be used directly as the output or reconstruction image at that level and as the error reconstruction image over lines 54 from reconstructor circuitry 48. Details of the Hierarchical Vector Quantization Encoding System Referring to Figure 11, the resolution pyramid is formed, as noted above, by decimating four times, in this illustrated embodiment, the highest resolution level of the image. In the one dimensional relationship illustrated in Figure 11, each pair of pixels at a lower level are averaged to form a single pixel at an upper level. The situation is the same both horizontally and vertically so that each higher level picture element is located at the center of a 2x2 pixel group of the lower level. The coding method also provides for generating, using an interpolation procedure, the pixels at a lower level from a higher level. The interpolation process is applied, for example, to the warped and reconstructed images to obtain images for processing at the next lower level and is effected by a bilinear interpolation. The interpolation factors are 0.75 and 0.25. In the illustrated embodiment of the invention, arithmetic coding is employed for both coding of information for transmission from the lossy compressor 28 as well as, and as will be discussed in more detail below, the coding of scalar data from lossy compressor 46. Arithmetic coding is well known to those skilled in the art. In particular, it can be applied advantageously to describing the locations of non-zero transform or other array variables. The symbol probabilities are changed depending upon previously transmitted values and the sequence position of the coefficient. Prestored probabilities are employed since on-line adaptation does not, in the experience of the inventor, provide significant improvement in this application. Considering the encoding of the resolution pyramids in more detail, and referring to Figure 12, the original and warped images have, at the top level, a resolution of 15x16 pixels for the luminance and 8x8 pixels for the chrominance, respectively. Figure 12 describes the processing of the luminance component; and the processing of the chrominance component (not shown) can be similarly illustrated. The prediction image consists of the top level warped image that was obtained originally by four decimations of the warped luminance and chrominance images, respectively. The prediction error is generated by subtracting the prediction image 510 from the original, uncoded, top level decimated image 512. The image differences over line 514 are quantized by a scalar quantizer 516 having a fixed step size. The quantized information over line 518 is encoded separately for each component, the Y, the I, and the Q components, using the same arithmetic encoder 520 which is also employed for the motion vector transform coefficients. Encoder 520 uses a Markov Model for encoding the non-zero data locations. The encoder has sixteen states depending upon whether the already encoded four nearest neighbors corresponding to the four nearest neighbors illustrated in Figure 8 are zero or non-zero. The non-zero values are encoded by a memory-less coder that encodes the eight bit quantization indices into the bit stream. The quantized difference image is added to the prediction as noted above, and the result is the output or reconstruction image (over lines 522) at the top level. The scalar quantizer 516 used in connection with the top level prediction error is a uniform quantizer having a dead-zone around zero- The thresholds (T(i)) are located at: T(i) = i*T i=1,2....,N The reconstruction levels (R(i)) are defined by: R(0) = 0 R(i) = (i+Delta*R) i=1,2,...,N Therefore, a value of X, where X is greater than T(k) but less than T(k+l) is assigned a quantizer index value of k and is reconstructed at the receiver as having a value R(k). The quantizer is also symmetric around zero and sets all values with a magnitude less than T(1) equal to zero. In accordance with the preferred embodiment of the invention, after quantization in accordance with the equation above has taken place, the quantizer 516 eliminates small non-zero values which are surrounded by all zero values. The criterion for setting a value to zero is that it has been quantized to the smallest non-zero amplitude (that is, a quantizer index of plus or minus one) and that its eight connected neighbors are quantized to a value of zero. This procedure increases the addressing efficiency of the arithmetic coder 520 and diminishes the impression of randomly appearing or "popping" blocks in an image. For the lower levels of the resolution pyramid, the prediction image is generated by combining the output image from the next higher level with the warped image of the same level. Then, the prediction error is formed by taking the difference of the original image at the current level. The difference image is coded using a gain/shape vector quantizer and the quantized difference is added to the prediction to obtain a new output image at the current level. The Y, I, and Q components are treated as three separate images. Considering the lower levels in more detail, the prediction image is generated by combining the warped image at the current level with the output and warped images from the next higher level. Specifically, the interpolation error of the warped image is generated using the warped image 524 at the current level and an interpolated version of the warped image from the next higher level (interpolated by circuitry 526). That interpolation error is thus the difference between the current level warped image and the same image that has been decimated and interpolated. As noted above, it contains the details of the warped image that were lost in the decimation to form the next higher level image. The output image from the next higher level is then interpolated at interpolation circuitry 527 to obtain an image at the current level. Thereafter, the warped interpolation error over line 528 is conditionally added by adder 530 to the interpolated output image to form the prediction. That is, for each block of 8x8 pixels, the squared error is determined between the original image stored at 532 and two possible predictions, that is, between the interpolated output image from the next higher level with and without the inclusion of the warped interpolation error. The elimination of the warped interpolation error is equivalent to low pass filtering the warped image for the prediction. This effective filtering process is performed in all blocks where it provides a significant decrease in the prediction error, that is, in those blocks wherein motion compensation was not successful. The result of the filtering process, termed "blurring," is effected if the "blurred error," multiplied by a weighting factor, such as 1.5 in the illustrated embodiment, is less than the error using the warped interpolation error. Further, if an 8x8 block is blurred at one level, the blurring will be applied at all lower levels corresponding to that part of the image. That is, at the next lower level the blurring will effect an area of 16x16 pixels and at a yet lower level it will effect an area of 32x32 pixels. The blur information generates a one-bit word for each 8x8 block. For example, a one indicates blurring and a 'zero indicates no blurring. The information is encoded using an arithmetic coder 534 such as that noted earlier, and since each word contains only one bit, there is no need to encode the non-zero values once the "blur location map" has been encoded. The particular arithmetic encoder 534 for the blur information uses five binary variables to select one of thirty-two states with corresponding probabilities. The binary variables are the four previously encoded blur words for neighboring blocks at the same level and the blur word for the higher level neighbor, that is, the block at the next higher level that corresponds to the current block. Thus, the encoder 534 does not make explicit use of the fact that blurring at one level propagates to lower levels and instead this relationship is reflected in the probabilities for the various states having a non-zero higher level neighbor. The prediction errors themselves are coded by a vector quantizer 536. Thus, at each level, the Y, I, and Q components are treated as three separate images. Each different image, generated for each level, is thus divided into blocks of 4x4 pixels. Each block then becomes the "vector" and is coded by the gain/shape vector quantization by first determining the best fitting shape and thereafter applying the appropriate gain. The shape code book contains normalized vectors (selected according to the LBG algorithm as is well known in the art) and the optimum shape vector is that code book vector which has the highest correlation with the data vector to be quantized. That is, the inner product of the data vector has a maximum for the optimum shape vector. The data vector is reconstructed at the receiver as the selected shape vector multiplied by a gain factor. The gain which gives the smallest squared error for the selected "shape" vector is quantized by selecting a reconstruction value from the gain code book. This is the scalar quantization noted above. For computational reasons, an exhaustive search of the shape code book, which typically has L=2**D shape vectors (when D equals 12 or 13), is not practical in real time. Instead, a binary tree search, which requires D+1 inner products to be generated (as compared to 2**D inner products for an exhaustive search) is employed. At each level of the tree search, the inner product is generated between the data vector and a prestored difference between two shape vectors. The decision depends on whether the inner product is positive or negative; and when all D levels of the binary tree search have been traversed, the shape vector has been determined. Thereafter, the inner product between the selected shape vector and the data vector is generated to obtain the gain factor. This search procedure is well known in the art. In the illustrated embodiment, the binary code book of size 2**D actually consists of a collection of code books of different sizes for each level; and at level M there exists a code book of size 2**M, M=1,2,...,D. In the vector quantizer 536, this structure is used to vary the shape code book size depending upon the gain factor. Thus, a smaller code book of size 2**D1, where D1 is less than D, is used for blocks where the gain was quantized to the smallest non-zero value, R(1). In blocks where the gain is larger, however, a full sized code book is used. As noted above, the gain factors are quantized by a uniform quantization to provide an index having a maximum value of 2**B. Isolated ones, as noted above, are eliminated, and encoding is performed using an arithmetic coder. The non-zero locations are encoded using five binary variables (thirty-two states) which include the four previously encoded neighbors at the same level and the higher level neighbor that is also available to the receiver as well as to the transmitter. The non-zero B-bit values are encoded by a memory-less encoder. The shape vectors are encoded using fixed length codes. For each non-zero gain value therefore, the shape vector needs to be transmitted. For gain values greater than one, D bits describe the shape vector, while for gains with a quantizer index equal to one, the smaller code book requiring D1 bits is used. When shape/gain vector quantizer encoding is applied repeatedly to the same image to build up the image to its full resolution, the coding becomes less and less efficient. This occurs not only because the coding error itself becomes more noise-like, but also because the code book becomes exhausted of "good vectors." Thus, the coding error rapidly becomes "orthogonal" to the code book. This effect is, in accordance with the claimed invention, significantly reduced by changing the image block boundary locations from frame to frame. Therefore, at the bottom levels, the blocks are shifted from frame to frame a few pixels, preferably along both the horizontal and vertical axes. This process substantially increases efficient coding in the system. The remaining levels can be encoded using the procedures applied at the (30x32) level, and using equivalents of elements 524, 526, 527, an adder 538, and elements 530, 534, and 536, but with the exception that the image data will be encoded, in the preferred embodiment, as described below. In accordance with the preferred embodiment of the invention, at the top level, the system does not provide any adaptive blurring and pure scalar quantization is employed. At the next level, the 32x30 level for the Y component and the 15x16 level for the chrominance components, the warped interpolation error is selectively added to the interpolated output images from the top level and therefore, at this level, blur information is transmitted. However, in the preferred embodiment of the invention, no encoding of the image information, that is, of the output image error, is performed in the illustrated embodiment. The prediction images themselves are the outputs from this level. In the three bottom levels, all of which are treated identically, adaptive blurring is used when generating the prediction images, and the prediction error is encoded using gain/shape vector quantization. This is indicated diagrammatically in Figure 12. The primary strategy for the encoding process is to use a fixed number of bits to encode each frame. The encoding starts at the top level and works through the pyramid level structure to the bottom level; and at all levels except the bottom level fixed quantizers are employed. For each level, the quantizer characteristics are selected based upon subjective image quality criteria. At the bottom level, however, the quantizer is chosen so that the number of generated bits is approximately equal to the number of bits still available for the frame. However, during heavy motion, all of the available bits may be used before the bottom level is reached. In that instance the quantizer for, for example, the next to lowest level can be selectively adjusted to provide the desired number of output bits for the frame. Thus at the bottom level, while the prediction is still generated in the usual way and the blur information is encoded and transmitted, no vector quantization is performed and instead the prediction image itself is the output image. In the illustrated embodiment, there can occur some circumstances, for example a scene change, when it may not be possible to encode even the next to lowest level. In that instance, the coding will stop at the next level up (60x64 for luminance and 30x32 for chrominance). If the coding at this level generates more bits than the desired number of bits per frame, the coding is still performed and the frame rate will temporarily slow down due to the large number of bits being generated. For the two bottom levels, the prediction is generated as usual and the blur information is transmitted; however, vector quantization is not performed. Referring to Figure 3, at the receiver 21, the transmitted and coded data is decoded and the new frame generated. In particular, the data representing the resolution pyramids is decoded by reconstruction circuitry 76 level by level from the top of the pyramid down to the bottom. At the top level, the quantized difference image is decoded and added to the warped image at that level (in selective adder 100 which includes decimation circuitry). Thereby, the output image at the top level is reconstructed. The lower levels are then reconstructed (by adder 100) by first forming the prediction using the transmitted blur information available over lines 84 from reconstruction circuitry 76 and then decoding the difference image and selectively adding it to the prediction image to form a new reconstructed image for that level. The process continues until the bottom level is reached and the bottom level image is transferred to the display frame buffer 98. The arithmetic decoder which is used in a number of processes, that is, decoding the motion transform coefficients, the blur information, and the image information from lossy compressor 46, operates as is well known in the art. Since the non-zero locations were encoded using different probabilities depending upon which state the coder was in, the arithmetic decoder regenerates the state for each position in the location map as the decoding proceeds. The state, in combination with the encoded data, then determines whether or not a zero is used for each map location. Once the map indicating the location of non-zero values has been decoded, the B-bit values are decoded and incremented by one and placed in the appropriate positions in the map. Looking in more detail at the generation of the resolution pyramids and decoding thereof, the process follows the inverse of the method used in lossy compressor 46. Thus, since the receiver decoding process follows the encoding process of the transmitter 8, the prediction at the top level is generated from the warped top level image. The quantizer indices are decoded using the arithmetic decoder and the quantized difference image is reconstructed from the quantizer indices and is then added to the prediction image to give the top level output image (corresponding to adder 522a and the output over lines 522 of the transmitter 8). At the lower levels, the prediction is formed by selectively adding the warped interpolation error to the interpolated output image from the next higher level (corresponding to adder 530 in the transmitter). That output image, and the warped image at the next output level, are interpolated to give images at the current level. The blur information is decoded using the arithmetic decoder and then, in each 8x8 block of the interpolated higher level output for which the blur code is zero, the difference between the current level warped image and the interpolated higher level warped image is added (corresponding to adder 538 of the transmitter). All the lower levels, according to the preferred embodiment of the invention, the vector quantized information is decoded first by decoding the gain values using the arithmetic decoder, and then, for the non-zero values, decoding the shape indices. For every block with a gain quantizer index of one, a D1-bit word is extracted from the bit stream to indicate the shape vector, while for blocks with an index greater than one, a D length bit word is extracted from the bit stream. The difference image is reconstructed by taking the shape vector from the appropriate code book and scaling it by the gain value. This is done for each non-zero 4x4 pixel block. The output image is thereafter formed by adding this reconstructed difference to the prediction. (This corresponds to the operation of the adder 540 of the transmitter.) The output image from the bottom level in the final reconstructed image is then transferred to the display frame buffer as the final output image. The illustrated lossy compressor 46 can be implemented in hardware, in software, or in a combination thereof. The Motion Estimator Referring now to Figure 6, in accordance with the illustrated embodiment, the motion estimation circuitry 26 employs an iterative spatial domain approach which quickly converges through an error minimization process for determining the displacement vectors of an input signal. In the preferred embodiment, an adaptive, steepest descent approach method is employed. The method has good convergence behavior. In Hinman, B., "Theory and Application of Image Motion Estimation," Master's Thesis, M.I.T. (1984), equation 3.12 describes the iterations for determining a displacement vector v for a pixel having a location p in an image f. The new image is represented by g. That equation is reproduced herein as Equation 3 where the "i" represents an earlier value of the displacement vector and "i + l" represents a next value of the displacement vector. Equation 3 can be implemented in accordance with Figure 6 where the input g and f frames are stored in buffers 200 and 202 respectively. The gradient value of the frame is determined by a gradient computer 204 and spatial interpolators 206, 208 provide the values of required by the summation in Equation 3. A summing element 210 and a multiplication element 212 yield the error gradient value which is accumulated in an accumulator 214. The output of the accumulator 214 is multiplied by a step size adaptor 215 at a multiplier 216; and the result is used to update the vector displacement value in an accumulator 218. The accumulator 214 receives the initial vector prediction value from a prediction hardware 220. The updated vectors are employed by interpolators 206 and 208 in determining the values of "f" and the vector output field is stored in a buffer 222. The entire apparatus operates under the control of a system controller 224 which monitors the value of the error gradient accumulator output and in response thereto adaptively changes the step size. Referring now to Figure 7, an improved method for implementing the adaptive steepest descent error minimization iterative spatial-domain motion estimator 26, defined by Equation 3, provides for use of a single interpolator 240 operating upon the f frame and a gradient computation circuitry 242 then operating upon the interpolated value output of interpolator 240. There results from this circuitry 242 the elimination of one of the Figure 6 interpolators thus providing a savings of hardware and/or software. In employing this method, the three important parameters are the initial step size, e, the stopping or cutoff threshold, T, and 'the predictor set, a k . The initial step size plays an important role in determining the rate at which the method converges upon the motion vector displacement. When e is chosen to have a very small value, the method requires an excessive number of iterations before reaching a sufficiently small neighborhood of the minimum. As the value of e increases, the rate of convergence also increases but there comes a value when e is so large that the search procedure will oscillate about the minimum without converging. The value of e must be determined by empirical tests. For a block size of 4x4, a value of 3x10 -5 has been found to provide the best convergence behavior. The cut-off threshold is compared to the magnitude of the error gradient times the initial step size, e, for each iteration. This threshold must be chosen with two constraints in mind. First, it should be sufficiently small so that a displacement close to the actual displacement is reached. The second and opposing constraint is that as the threshold decreases, the number of required iterations increases dramatically. Thus, as with the step size, the appropriate cut-off threshold must be found empirically. (When the step size varies, as described below, the threshold, T, as defined above continues to be compared against the multiplicative product of the initial step size, e, and the error gradient.) In determining the cutoff threshold empirically, two indicators are of interest. They are the average number of iterations per block and the motion compensated frame difference energy. In order to find the best value of T, the estimation and compensation process is run several times. Starting with a small cut-off threshold, a minimal value of the motion compensated frame difference energy is determined. As the threshold is increased, the average number of iterations steadily drops while the motion compensated frame difference energy remains essentially constant. Eventually, however, a value of the threshold is reached at which the estimated displacements become inaccurate and the motion compensated frame difference energy begins to rise. In seeking the point of inflection in the motion compensated frame difference energy as a function of T, a value of 7x10 -3 was found to be most appropriate. This threshold corresponds to a minimum vector-update of 7x10 -3 pixels. The selection of the predictor coefficients affects both the average number of iterations and the motion compensation frame difference energy. The selection of the initial value of the displacement vector for each block is, in the illustrated embodiment, chosen as a linear combination of displacement vectors adjacent thereto. Thus, referring to Figure 8, the steepest descent method provides access to the displacement vectors above and to the left of a present displacement vector V O . Thus, in accordance with the illustrated embodiment, the present displacement vector is defined by Equation 4 as: The a j are the predictor coefficients while the V j are the previously determined displacement vectors. The preferred vector predictors, a j , are a 1 = 0.3, a 2 = 0; a 3 = 0.4 and a 4 = 0.3. For these values of the vector predictors, in combination with the step value and threshold values noted above, for one set of data, the average number of iterations was 6.71, and the motion compensation frame difference energy was 14.1 dB's lower than the non-motion compensated frame difference energy. In accordance with a preferred embodiment of the invention, the selected value of e, the initial step size can be adapted to change as a function of the error gradient. Thus, according to this illustrated embodiment of the invention, and under the control of the system controller 224, the step size value is adapted to change, depending upon the present gradient error value, or the present and one or more previous error gradient values, so that the step size for the vector displacement does not become unreasonably small. A description of two methods for selecting step size is provided in the Hinman thesis beginning at page 33. According to the preferred embodiment of the invention, the second method, defined by Equations 3.18, 3.19, and 3.20 of the Hinman thesis is modified to reduce the processing load of the system. In this embodiment, the equations 3.18, 3.19, and 3.20 are modified so that: (new step size) = (old step size) · ∝ where 1.4 if R > 0 ∝ = 0.3 if R < 0 and R = [Gradient E(V i x )] · [Sign [Gradient E(V i-1 x )]] + [Gradient E(V i y )] · [Sign [Gradient E(V i-1 y )]] and "Gradient E" represents the gradient of the present x or y error function, and "Sign [·]" equals ±1 depending upon the sign of the argument. Equation 6, thus defined, provides a third method for an adaptive steepest descent approach. As noted above, however, the cutoff threshold value, T, is measured against the initial step size. Thus, the illustrated T can be defined as the product of a constant times the error gradient. Further, in accordance with the preferred embodiment of the invention, the system controller 224 also prevents the displacement increment step size from being greater than a selected threshold, for example, greater than one pixel, and further prevents the maximum value of the displacement vector from being greater than a second selected threshold, for example greater than 7 1/2 pixels. In this manner, more control of the steepest descent process is available and singularities which prevent convergence can be avoided. The illustrated motion estimator can be implemented in hardware, in software, or in a combination thereof. In one particular embodiment, attached hereto as Appendix C, a software implementation of an adaptive steepest descent method and apparatus is provided. Adaptive Filter Embodiment Referring to Figure 13, in another illustrated embodiment of the invention, the blur information provided by the lossy compressor 46 is eliminated and in its place is provided a selectively operable adaptive filter 700. In the operation of this embodiment of the invention, for those blocks wherein the motion compensation data is accurate, the signal over lines 56 is applied directly, by the adaptive filter 700, to its output over lines 702. For those blocks for which motion compensation is not adequate, as described in more detail below, the adaptive filter can, in effect, low-pass filter the output data over lines 56 for the block and provides over lines 702, for those regions wherein filtering is advantageous, a low-pass version of the motion compensation reconstructed receiver image for the block. In addition, the adaptive filter 700 provides filter data, over lines 704, to the channel encoder 18 for transmission to the receiver 21 as side information. Referring to Figure 14, the receiver 21 decodes the filtering information and provides a filter data signal over line 708. The remaining circuitry of the receiver 21 in Figure 14 operates in a manner corresponding to that illustrated in Figure 3 except that the filter data signal determines whether the motion compensation data for a block will be low pass filtered prior to use. In accordance with this embodiment of the invention, therefore, the hierarchical encoding method receives data which is filtered prior to receipt. Accordingly, the encoding method does not, in this illustrated embodiment, provide further blur information which would in large part be redundant to the adaptive filtering data being already transmitted to the receiver. Considering the adaptive filter in more detail, as noted above, the output of the motion compensator 42 represents the receiver motion compensated image as a result of applying the coded motion signal representation from the lossy compressor 28 to the previous frame which is stored in frame buffer 44. The receiver motion compensated image, under certain circumstances, can be improved in various spatial regions (blocks) by selectively applying a spatial low-pass filter. To decide whether the filtering process should be performed on a block of the receiver motion compensated image, a comparison of the squared prediction error between the original image and the unfiltered and filtered prediction is performed on a block-by-block basis. A block, in this illustrated embodiment, is designated as an 8x8 grouping of picture elements. For each block, the prediction having the least error energy (weighted, for example, by a constant to provide a bias in favor of unfiltered prediction) is selected, and that decision information, the filter data available over line 704, is made available to the encoder 18. The filter data is sent to the receiver to enable it to perform the same operation as the transmitter 8 on each corresponding block during the receiver image reconstruction process. The receiver 21 decodes and provides the filter data to motion compensator 99 over lines 708. After the adaptive low-pass filtering decision has been made for a block, the resulting block image, whether or not filtered, is employed, as noted above, as the estimated receiver image over lines 702. The adaptive filter has four stages of operation. First, the block is low-pass filtered. Second, an energy measurement is made for both the filtered and unfiltered versions of the block in comparison to the original image. Third, a decision is made to determine if the low-pass filtered block should be inserted in place of the unfiltered receiver motion compensated image. Finally, the information describing the filter usage for each block is encoded (the filter data on lines 704) and sent to the encoder 18. Further details of the adaptive filter operation are described in US-A-4,816,914 referred to hereinabove. The hierarchical encoding method and apparatus described hereinabove can also be advantageously employed in connection with the transmission of a sequence of images in which motion compensation is not provided. In this instance, the estimated receiver image over, for example, lines 51 in Figure 2 will be the reconstructed receiver image designated as the frame output of the frame buffer 44 over lines 64. Further, the input image over lines 22 and the estimated receiver image over lines 51 need not be individually decimated by lossy compressor 46 but can be, referring to Figure 15, input to a difference circuitry 720, the output of which, representing the error signal at the receiver, can then be input to a lossy compressor for decimation and hierarchical encoding in accordance with the invention described hereinabove. At the receiver, the motion compensator 99 and its related circuitry would similarly be eliminated if motion compensation were not employed. Similarly, the reconstruction circuitry 76 would be modified in accordance with the transmitter operation to reconstruct the error image representation over lines 84 when the circuitry of Figure 15 is employed. These changes would be apparent to those practiced in the art. Additions, subtractions, deletions, and other modifications of the preferred particular embodiments of the invention will be apparent to those skilled in the art and are within the scope of the following claims.

Claims: A method of encoding data values for representing image data in an image transmission system, represented as a multi-dimensional array of data values, comprising the steps of:- quantizing the said data values, setting to a zero value all quantized data values having a zero value for each of its nearest neighbors, and applying vector quantization coding to the remaining data values. A method according to claim 1, characterised in that the array is a two dimensional array and has eight nearest neighbors. A method according to claim 2, characterised by the step of motion compensating the image transmission system for transmitting a sequence of images over a communications path.

Inventors: ERICSSON S STAFFAN, ERICSSON, S. STAFFAN
Applicants: PICTURETEL CORP, PICTURETEL CORPORATION
Application year: 1988
Main classification: H04N7
IPC codes: H04N7, G06T9