Showing papers on "Data compression published in 1989"

Two-layer coding of video signals for VBR networks

Abstract: Two-layer conditional-replenishment coding of video signals over a variable-bit-rate (VBR) network is described. A slotted-ring network based on an Orwell protocol is assumed, where transmission of certain packets is guaranteed. The two-layer coder produces two output bit streams: the first bit stream contains all the important structural information in the image and is accommodated in the guaranteed capacity of the network, while the second adds the necessary quality finish. The performance of the coder is tested with CIF standard sequences and broadcast-quality pictures. The portion of the VBR channel allocated to the lower layer as guaranteed bandwidth is examined. Using broadcast-quality pictures, statistics were obtained on the performance of this system for different choices of bit rate in the lower layer. The effect of lost packets is shown on CIF standard picture sequences. It is shown that the coder performs well for a guaranteed channel rate as low as 10-20% of the total bit rate. >

A perceptually tuned sub-band image coder with image dependent quantization and post-quantization data compression

Abstract: The authors present a 16-band subband coder arranged as four equal-width subbands in each dimension, It uses an empirically derived perceptual masking model, to set noise-level targets not only for each subband but also for each pixel in a given subband. The noise-level target is used to set the quantization levels in a DPCM (differential pulse code modulation) quantizer. The output from the DPCM quantizer is then encoded, using an entropy-based coding scheme, in either 1*1, 1*2, or 2*2 pixel blocks. The type of encoding depends on the statistics in each 4*4 subblock of a particular subband. One set of codebooks, consisting of less than 100000 entries, is used for all images, and the codebook subset used for any given image is dependent on the distribution of the quantizer outputs for that image. A block elimination algorithm takes advantage of the peaky spatial energy distribution of subbands to avoid using bits for quiescent parts of a given subband. Using this system, high-quality output is obtainable at bit rates from 0.1 to 0.9 bits/pixel, and nearly transparent quality requires 0.3 to 1.5 bits/pixel. >

Coding of arbitrarily shaped image segments based on a generalized orthogonal transform

Abstract: Region oriented image representation offers several advantages over block-oriented schemes, e.g. adaptation to the local image characteristics, or object motion compensation as opposed to block-wise motion compensation. For the task of image data compression, i.e. image coding, new algorithms are needed which work on arbitrarily shaped image regions, called segments, instead of rectangular image blocks. Based on a generalized moment approach, the luminance function inside the segment is approximated by a weighted sum of basis functions, for example polynomials. A set of basis functions which is orthogonal with respect to the shape of the segment to be coded can be obtained using orthogonalization schemes. This results in the derivation of a generalized shape-adapted transform coder. Suitable coder and decoder structures are introduced which do not necessitate the transmission of the basis functions for each segment. Finally an application of the derived algorithms to image sequence coding at low data rates is shown, which is based on a segmentation of the motion compensated prediction error image.

Data compression with finite windows

Abstract: Several methods are presented for adaptive, invertible data compression in the style of Lempel's and Ziv's first textual substitution proposal. For the first two methods, the article describes modifications of McCreight's suffix tree data structure that support cyclic maintenance of a window on the most recent source characters. A percolating update is used to keep node positions within the window, and the updating process is shown to have constant amortized cost. Other methods explore the tradeoffs between compression time, expansion time, data structure size, and amount of compression achieved. The article includes a graph-theoretic analysis of the compression penalty incurred by our codeword selection policy in comparison with an optimal policy, and it includes empirical studies of the performance of various adaptive compressors from the literature.

Computer-based video compression system

Abstract: A computer-based video compression system for processing natural information signals, such as video signals or audio signals, for the purpose of forming a compact data file of compressed signals which can be expanded to produce the original information signals is provided by a unique subsystem in a host computer which uses a high speed signal processor to compress video images and to expand video images. The unique compression process uses segmentation and predictive techniques in conjunction with a discrete sine transform, quantization and Huffman coding to provide optimal compression. Further the segmentation and predictive techniques in conjunction with the discrete sine transform diminish the magnitude of correlated errors generated by the compression process. The compression system of this invention is further enhanced by a special circuit which transfers data between the host computer and the compression subsystem at rates greater than were previously possible.

Word-based text compression

Abstract: The development of efficient algorithms to support arithmetic coding has meant that powerful models of text can now be used for data compression. Here the implementation of models based on recognizing and recording words is considered. Move-to-the-front and several variable-order Markov models have been tested with a number of different data structures, and first the decisions that went into the implementations are discussed and then experimental results are given that show English text being represented in under 2-2 bits per character. Moreover the programs run at speeds comparable to other compression techniques, and are suited for practical use.

Method for high-quality compression by binary text images

Abstract: The invention relates to a method for the compression and decompression of binary test images. The method distinguishes between large low-frequency areas and small high-frequency areas in the original frame. For the low-frequency areas, a scheme for lossy compression is used, whereas for the high-frequency areas, a scheme permitting lossless compression is applied. The compression/decompression process involves five stages; namely prefiltering to remove all black patches (e.g. by removing all black pixels, except where they belong to a large black segment), fast evaluation of compressibility by partitioning the images into mutually exclusive segments and applying different compression modes to each segment, connectivity-oriented subsampling to reduce the reslolution in horizontal and vertical directions which cause the image to be segmented into blocks and a 1-pixel representation for each block is determined, lossless compression and decompression where the reduced file is compressed by conventional techniques, and reconstruction by sequence reversal so that lossless decompression will retrieve the subsampled file, expansion of the subsampled file through replacement of each pixel by a block having equal value and postfiltering.

Entropy reduction and decorrelation in visual coding by oriented neural receptive fields

Abstract: In biological visual systems, it is not obvious whether coding efficiency as measured by mutual information among the neurons is a factor that explains any of their properties. The center/surround receptive field profiles of neurons in the retina and geniculate are far from an orthogonal set, but a given neuron can still be regarded as a decorrelator of the incoming signal in the sense that it responds primarily to changes in the image. At the level of the brain's visual cortex, the introduction of the new variable of orientation selectivity can be regarded not only as a means for providing orientation labels for image structure, but also more basically as an effective decorrelator of the neural representation. The present image coding simulations, based on quantitative neurobiological data about the code primitives, provide measures of the bit-rate efficiency of such oriented, quadrature, neural codes. Demonstrations of data compression to below 1 bit/pixel in cortically-based, quadrature self-similar wavelet image codes are also provided. >

On the estimation of the order of a Markov chain and universal data compression

Abstract: The authors estimate the order of a finite Markov source based on empirically observed statistics. The performance criterion adopted is to minimize the probability of underestimating the model order while keeping the overestimation probability exponent at a prescribed level. A universal asymptotically optimal test, in the sense just defined, is proposed for the case where a given integer is known to be the upper bound of the true order. For the case where such a bound is unavailable, an alternative rule based on the Lempel-Ziv data compression algorithm is shown to be asymptotically optimal also and computationally more efficient. >

Data compression with dynamically compiled dictionary

Abstract: A data compression system in which a dictionary stored strings of characters and an encoder matches the longest of the stored string with a current string of a data stream input to the encoder. The index of the longest matched stored string is output by the encoder and the dictionary is updated by a new string consisting of the previous match concatenated with the first two characters only of the present match. If the present match has only one or two characters, it is added without reduction.

Adaptive data compression apparatus including run length encoding for a tape drive system

Abstract: The adaptive data compression apparatus is located within a tape drive control unit which is interposed between one or more host computers and one or more tape transports. The adaptive data compression apparatus functions to efficiently compress a user data file received from a host computer into a bit oriented compressed format for storage on the magnetic tape that is loaded in the tape transport. The data compression apparatus divides each block of an incoming user data file into predetermined sized segments, each of which is compressed independently without reference to any other segment in the user data file. The data compression apparatus concurrently uses a plurality of data compression algorithms to adapt the data compression operation to the particular data stored in the user data file. A cyclic redundancy check circuit is used to compute a predetermined length CRC code from all of the incoming user data bytes before they are compressed. The computed CRC code is appended to the end of the compressed data block. The data compression apparatus operates by converting bytes and strings of bytes into shorter bit string codes called reference values. The reference values replace the bytes and strings of bytes when recorded on the magnetic tape. The byte strings have two forms, a run length form for characters that are repeated three or more times, and a string form that recognizes character patterns of two or more characters.

Image signal recording apparatus capable of recording compressed image data together with audio data

Abstract: An image signal recording apparatus achieves an orthogonal transform and a compression coding on image data so as to record the resultant data in a recoding medium. There is disposed a selector to select a compression ratio for the compression coding of the data, namely, the compression ratio is selectable. The selected compression ratio data is recorded in the recording medium together with the image data. A playback apparatus reads from the recording medium the compression ratio data together with the image data undergone the compression coding so as to decode the image data by use of the compression ratio data. In consequence, according to these apparatuses, the compression ratio can be arbitrarily set. In addition, the image signal recording apparatus generates recording codes associated with the amounts of the image data and the audio data so as to write the codes in the recording medium. The recording codes are read from the recording medium, so that the remaining amount of the recording medium available for the recording operation is displayed.

Data compression system for successively applying at least two data compression methods to an input data stream

Abstract: The improved data compression system concurrently processes both strings of repeated characters and textual substitution of input character strings. In this system, the performance of data compression techniques based on textual substitution are improved by the use of a compact representation for identifying instances in which a character in the input data stream is repeated. This is accomplished by nesting a run length encoding system in the textual substitution system. This structure adds the recognition of runs of a repeated character before the processor performs the textual substituted data compression operation. A further performance improvement is obtained by expanding the alphabet of symbols stored in the compressor's dictionary to include both the characters of the input data stream and repeat counts which indicate the repetition of a character. The handling of these repeat counts by the textual substitution based compression technique is no different than the handling of characters, or certain modifications are made in the handling of repeat counts.

Adaptive zonal coder

Abstract: The invention provides a method and apparatus for performing image data compression. Initially, a two-dimensional block of image data in a spatial domain is transformed by a transform coder, resulting in a two-dimensional array of activity coefficients in a frequency domain. The array is then serialized and quantized, yielding a one-dimensional array of coefficients with a leading coefficient and an original trailing coefficient. Next, a portion of the array is selected by choosing a new trailing coefficient based on a setable ratio of the energy of the new short array to the energy of the original array. Lastly, an end-of-block symbol is appended after the new trailing coefficient, and the selected portion of the array is encoded using an entropy coder. The invention allows image data to enjoy enhanced compression with good image fidelity, and allows image fidelity to degrade gracefully in trade for higher degrees of image compression.

Adaptive transform coding via quadtree-based variable blocksize DCT

Abstract: An adaptive transform coding algorithm using a quadtree-based variable blocksize DCT (discrete cosine transform) is introduced to achieve a better tradeoff between bit rate and image quality. The choice of appropriate blocksize is determined by a mean-based decision rule that can discriminate various image contents for better visual quality. Some simulation results are given. It is found that the same or better image quality can be obtained with lower average bit rate. >

Image data compression using a neural network model

Abstract: Data compression and generalization capabilities are important for neural network models as learning machines From this point of view, the image data compression characteristics of a neural network model are examined The applied network model is a feedforward-type, three-layered network with the backpropagation learning algorithm The implementation of this model on a hypercube parallel computer and its computation performance are described Image data compression, generalization, and quantization characteristics are examined experimentally Effects of learning using the discrete cosine transformation coefficients as initial connection weights are shown experimentally >

Algorithm 673: Dynamic Huffman coding

Abstract: We present a Pascal implementation of the one-pass algorithm for constructing dynamic Huffman codes that is described and analyzed in a companion paper. The program runs in real time; that is, the processing time for each letter of the message is proportional to the length of its codeword. The number of bits used to encode a message of t letters is less than t bits more than that used by the well-known two-pass algorithm. This is best possible for any one-pass Huffman scheme. In practice, it uses fewer bits than all other Huffman schemes. The algorithm has applications in file compression and network transmission.

Encoding of images based on a lapped orthogonal transform

Abstract: Traditional block transform image coding systems generate artifacts near block boundaries which degrade low bit rate coded images. To reduce these artifacts, a class of unitary transformations, called lapped orthogonal transforms (LOT), is investigated. The basis function on which the signal is projected are overlapped for adjacent blocks. An example of an LOT optimized in terms of energy compaction is numerically derived, using an augmented Lagrangian optimization algorithm. Using this LOT, intraframe coding experiments for 256*240 pixel images were performed at bit rates between 0.1 and 0.35 bits/pixel. The LOT improved the coded image subjective quality over other transforms. The LOT was also used in interframe full-motion video coding experiments for head and shoulder sequences at 28 and 56 kb/s. Significant improvement resulted at low data rates and if no motion compensation were used. However, the improvement was no longer significant at 56 kb/s with full motion compensation. >

Classified transform coding of images using vector quantization

Abstract: An adaptive image coding scheme, called classified transform vector quantization, is proposed. It efficiently exploits correlation in large image blocks by taking advantage of transform coding (TC) and vector quantization (VQ), while overcoming the suboptimalities of TC and avoiding the complexity obstacle of VQ. After local mean luminance values are removed in the spatial domain using two-stage interpolative VQ, the residual errors are encoded in the transform domain by means of perceptual block classification and adaptive subvector construction. This scheme avoids the use of scalar quantization of DC coefficients in the transform domain and yet substantially reduces the blocking effect that tends to arise at low bit rates. Good reconstructed images have been obtained at rates between 0.3 and 0.4 bits/pixel, depending on the nature of the test images. The technique also permits progressive image transmission and reproduces errorless images with compression of about 5.0 bits/pixel. Experimental results indicate that an efficient bit allocation in the coding process produces a substantial improvement in performance. >

Image sequence compression by iconic indexing

Abstract: A method that facilitates the rapid retrieval of a given image sequence from a large database is presented. The authors exploit the fact that much of the information stored is redundant. They extend the two-dimensional string methodology to image sequences. This permits queries on the relative positions of objects within video sequences, including changes in position over time. >

Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

Abstract: The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

Search tree data structure encoding for textual substitution data compression systems

Abstract: Non-redundant encoding for textual substitution data compression systems is provided by encoding the structure of search tree constructed and maintained by the compressor for the compression of the source data, thereby enabling an encoder to reconstruct an identical search tree for expanding the data.

Data compression system and method with buffer control

Abstract: In a digital encoder, truncation is controlled by the fullness of the output rate-smoothing buffer A signal compression system is shown for processing a stream of fixed length digital sample signals, such as audio signals, which system includes a linear digital compression filter for compression filtering the sample signal stream and generating a stream of compression-filtered signals The compression-filtered stream is encoded by an encoder which implements a variable word length truncated code The encoder output is supplied to a buffer for transmission to a communication channel The encoder is controllably operable in a normal mode and in an out of range (OOR) mode In the OOR operating mode an OOR code word together with the compression filtered signal is sent to the buffer Buffer underflow is controlled by operation in the OOR mode when the buffer is empty or near empty Buffer overflow is controlled by truncating sample signals supplied to the compression filter in response to a measure of buffer fullness when the fullness of the buffer exceeds a predetermined level The level of truncation increases as buffer fullness increases With a decrease in buffer fullness, a measure of the rate of change of buffer fullness may be used to accelerate the decrease in truncation for improved audio signal quality Additionally, a measure of variance of the compression-filtered signal stream may be used in conjunction with control based upon a measure of buffer fullness in the control of truncation for improved audio signal quality

A fast MMSE encoding technique for vector quantization

Abstract: The authors present a very efficient minimum mean-squared error (MMSE) encoding method useful for vector quantization. Using this method results in a considerable reduction in the number of multiplications and additions. The increase in the number of comparisons is moderate, and therefore the overall saving in the number of operations is still considerable. Very little precomputation and extra storage is required. >

Universal data compression and repetition times

Abstract: A novel universal data compression algorithm is described. This algorithm encodes L source symbols at a time. An upper limit for the number of bits per source symbol is given for the class of binary stationary sources. In the author's analysis, a property of repetition times turns out to be of crucial importance. >

Apparatus and method for effecting data compression

Abstract: A dictionary-based data compression technique wherein compression occurs at a variety of levels in response to word, phrase, super-phrase (sentence), and context-sensitive recognition. A separate dictionary is used at each compression level so that word compression occurs first, followed by phrase compression, followed by other compressions. Disclosed applications built upon the compression strategy include an idiomatic-language translator and a voice-recognition control system.

Bi-level image coding with MELCODE-comparison of block type code and arithmetic type code

Abstract: It is shown how to encode and transmit binary Markov sources using a set of block codes called MELCODE. Fill symbol control is used to manage the transmission order of codewords with limitation of memory size. MELCODE is extended to arithmetic-type code, and the calculation accuracy of coding address is clarified. Block codes and arithmetic codes are compared in terms of memory size and coding efficiency through the simulation of bilevel image coding, showing an improvement in coding efficiency. >

Stereoscopic images disparity for predictive coding

Abstract: In order to create a 3-D system with two images (right and left) that must be transmitted simultaneously, an efficient coding appropriate for stereoscopic images must be developed to reduce the large amount of information contained in the images. As an initial step in realizing such a coding scheme, the statistical characteristics of stereoscopic images and the possibility of stereoscopic image data compression utilizing the cross correlation between the right and left images are considered. The results indicate that data compression is possible by shifting one image horizontally and subtracting it from the corresponding area of the other. Experiments to compare the capability of generating disparity by stereoscopic TV images and human stereoscopic vision have been performed. The results indicate that data compressions without 3-D image deterioration is possible by reducing high-spatial-frequency disparity above 3 cycles/degree. It is concluded that efficient image coding for stereoscopic images can be achieved by utilizing the correlation between two images and human stereopsis characteristics, making possible low-cost, more realistic 3-D visual communication. >