Since DPCM and transform coding are two fundamental approaches to high-efficiency (bit reduction) coding, it is important to clarify the basic coding characteristics of these approaches and the differences between the...
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Since DPCM and transform coding are two fundamental approaches to high-efficiency (bit reduction) coding, it is important to clarify the basic coding characteristics of these approaches and the differences between them in order to utilize the high-efficiency coding method effectively. It is important to compare them not only from the standpoint of coding performance as optimized coding schemes based on the statistics of the input picture signal, but also from that of the robustness of coding performance for the variation of picture statistics to be coded. This paper theoretically compares the robustness of the coding performance of DPCM having a two-dimensional predictor with that of a two-dimensional Hadamard transform coding in an intrafield coding method of the NTSC composite signal. The comparison provides theoretical evidence that transform coding is more stable than DPCM, and this tendency is marked at lower bit rates such as 1 or 2 bits/pel, while DPCM has a higher coding performance for pictures with high autocorrelation.
Hybrid predictive/transform coding is studied. The usual formulation is to first apply a unitary transform and then code the transform coefficients with independent DPCM coders, i.e., the prediction is performed in th...
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Hybrid predictive/transform coding is studied. The usual formulation is to first apply a unitary transform and then code the transform coefficients with independent DPCM coders, i.e., the prediction is performed in the transform domain. This structure is compared to spatial domain prediction, where a difference signal is formed in the spatial domain and then coded by a transform coder. A linear spatial domain predictor which minimizes the mean square prediction error also minimizes the mean square of each transform coefficient. The two structures are equivalent if the transform domain prediction scheme is extended to a more general predictor. Hence, the structure that gives the easiest implementation can be chosen. The spatial domain structure is preferred for motion compensation and for line interlaced video signals. Interframe hybrid coding experiments are performed on interlaced videophone scenes using an adaptive transform coder. Motion compensation gives a rate reduction of 25-35 percent compared to frame difference prediction with the same mean square error. The subjective advantage is even greater, since the "dirty window" effect is not present with motion compensation. It is important to perform the motion estimation with fractional pel accuracy. Field coding with a switched predictor using previous field in moving areas is an interesting alternative to frame coding with frame difference prediction.
Canonical correlations are used to decompose the Wiener filter into a whitening transform coder, a Canonical filter, and a coloring transform decoder, The outputs of the whitening transform coder are called canonical ...
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Canonical correlations are used to decompose the Wiener filter into a whitening transform coder, a Canonical filter, and a coloring transform decoder, The outputs of the whitening transform coder are called canonical coordinates;these are the coordinates that are reduced in rank and quantized in our finite-precision version of the Gauss-Markov theorem, Canonical correlations are, in fact, cosines of the canonical angles between a source vector and a measurement vector, They produce new formulas for error covariance, spectral flatness, and entropy.
The optimal linear block transform for coding images is well known to be the Karhunen-Loeve transformation (KLT), However, the assumption of stationarity in the optimality condition is far from valid for images, Image...
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The optimal linear block transform for coding images is well known to be the Karhunen-Loeve transformation (KLT), However, the assumption of stationarity in the optimality condition is far from valid for images, Images are composed of regions whose local statistics may vary widely across an image. While the use of adaptation can result in improved performance, there has been little investigation into the optimality of the criterion upon which the adaptation is based, In this paper we propose a new transform coding method in which the adaptation is optimal, The system is modular, consisting of a number of modules corresponding to different classes of the input data, Each module consists of a linear transformation, whose bases are calculated during an initial training period, The appropriate class for a given input vector is determined by the subspace classifier, The performance of the resulting adaptive system is shown to be superior to that of the optimal nonadaptive linear transformation. This method can also be used as a segmentor. The segmentation it performs is independent of variations in illumination, In addition,the resulting class representations are analogous to the arrangement of the directionally sensitive columns in the visual cortex.
This paper addresses the problem of finding a B-term wavelet representation of a given discrete function f is an element of R-n whose distance from f is minimized. The problem is well understood when we seek to minimi...
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This paper addresses the problem of finding a B-term wavelet representation of a given discrete function f is an element of R-n whose distance from f is minimized. The problem is well understood when we seek to minimize the Euclidean distance between f and its representation. The first-known algorithms for finding provably approximate representations minimizing general f, distances (including l(infinity)) under a wide variety of compactly supported wavelet bases are presented in this paper. For the Haar basis, a polynomial time approximation scheme is demonstrated. These algorithms are applicable in the one-pass sublinear-space data stream model of computation. They generalize naturally to multiple dimensions and weighted norms. A universal representation that provides a provable approximation guarantee under all p-norms simultaneously;and the first approximation algorithms for bit-budget versions of the problem, known as adaptive quantization, are also presented. Further, it is shown that the algorithms presented here can be used to select a basis from a tree-structured dictionary of bases and find a B-term representation of the given function that provably approximates its best dictionary-basis representation.
Techniques for fast image transform coding on 32-bit processors are described. The Reparameterized Suehiro transform is used to avoid multiplication;then two 16-bit arithmetic computations are accomplished simultaneou...
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Techniques for fast image transform coding on 32-bit processors are described. The Reparameterized Suehiro transform is used to avoid multiplication;then two 16-bit arithmetic computations are accomplished simultaneously with 'paired arithmetic'. This reduces the effective cost of the 8-point DCT-III to about 11 additions, 9 subtractions and 15 shifts. With these techniques the Sun Sparcstation can perform JPEG compression and decompression at rates of 45 and 80 million pixels per minute respectively.
In this paper, we describe a video coding design that enables a higher coding efficiency than the HEVC standard. The proposed video codec follows the design of block-based hybrid video coding, but includes a number of...
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In this paper, we describe a video coding design that enables a higher coding efficiency than the HEVC standard. The proposed video codec follows the design of block-based hybrid video coding, but includes a number of advanced coding tools. A part of the incorporated advanced concepts was developed by the Joint Video Exploration Team, while others are newly proposed. The key aspects of these newly proposed tools are the following. A video frame is subdivided into rectangles of variable size using a binary partitioning with variable split ratios. Three new approaches for generating spatial intra prediction signals are supported: A line-wise application of conventional intra prediction modes, coupled with a mode-dependent processing order, a region-based template matching prediction method and intra prediction modes based on neural networks. For motion-compensated prediction, a multi-hypothesis mode with more than two motion hypotheses can be used. In transform coding, mode dependent combinations of primary and secondary transforms are applied. Moreover, scalar quantization is replaced by trellis-coded quantization and the entropy coding of the quantized transform coefficients is improved. The intra and inter prediction signals can be filtered using an edge-preserving diffusion filter or a non-linear DCT-based thresholding operation. The video codec includes an adaptive in-loop filter for which one of three classifiers can be chosen on a picture basis. We also incorporated an optional encoder control, which adjusts the quantization parameters based on a perceptually motivated distortion measure. In a random access scenario, our proposed video codec achieves luma BD-rate savings between 32.5% for HDR HLG UHD and 39.6% for SDR UHD over the HEVC (HM software) anchor for different categories of test sequences.
transform coding has been applied successfully for radiological image compression in the picture archival and communication system (PACS) and other medical applications. However, the blocking artifact caused by the bl...
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transform coding has been applied successfully for radiological image compression in the picture archival and communication system (PACS) and other medical applications. However, the blocking artifact caused by the block implementation in conventional transform coding is undesirable in the clinical environment. A combined-transform coding (CTC) scheme is proposed in this paper to reduce this artifact and hence achieve better subjective performance. In the combined-transform coding scheme, the original image is first divided into two sets of image planes that have different stochastic properties. The upper image set (UIS) contains the most significant information and tends to be highly correlated, and the lower image set (LIS) contains the less significant information. The UIS is coded noiselessly without dividing into blocks and the LIS is coded by conventional block transform coding. Since the correlation in UIS is significantly reduced, the interblock correlation and hence the blocking artifact are reduced. This paper first describes the proposed CTC scheme and investigates its information-theoretic properties. Then computer simulation results for a class of AP view chest X-ray images are presented. The comparison between the CTC scheme and the conventional discrete cosine transform (DCT) and discrete Walsh-Hadmard transform (DWHT) is made to demonstrate the performance improvement of the proposed scheme. The concept of combined-coding is also used for perfect reconstruction of the class of chest X-ray images and slight improvement in the compression performance is observed. Finally, we point out that the CTC scheme has advantages in medical image transmission over a noisy channel or a packet-switched network in case of channel error and packet loss due to the layered structure of the proposed approach.
We construct general biorthogonal Coifman wavelet systems, a new class of compactly supported biorthogonal wavelet systems with vanishing moments equally distributed for a scaling function and wavelet pair, A time-dom...
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We construct general biorthogonal Coifman wavelet systems, a new class of compactly supported biorthogonal wavelet systems with vanishing moments equally distributed for a scaling function and wavelet pair, A time-domain design method is employed and closed-form expressions for the impulse responses and the frequency responses of the corresponding dual filters are derived, The resulting filter coefficients are all dyadic fractions, which is an attractive feature in the realization of multiplication-free discrete wavelet transform, Even-ordered systems in this family are symmetric, which correspond to linear-phase dual filters, In particular, three filterbanks (FB's) in this family are systematically verified to have competitive compression potential to the 9-7 tap biorthogonal wavelet FB by Cohen et al., which is currently the most widely used one in the field of wavelet transform coding. In addition, the proposed FB's have much smaller computational complexity in terms of floating-point operations required in transformation, and therefore indicate a better tradeoff between compression performance and computational complexity.
Adaptive multistage image transform coding is discussed and an optimal method is introduced for bit allocation. The optimality is in the sense of minimizing the mean square reconstruction error with a given total numb...
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Adaptive multistage image transform coding is discussed and an optimal method is introduced for bit allocation. The optimality is in the sense of minimizing the mean square reconstruction error with a given total number of bits and a given number of stages. The statistics of the coefficients in different stages and marginal analysis are used to optimize the division of the total number of bits among the stages. Experimental results indicate that, with two stages, more than 14% improvement for one clan and more than 11076 improvement for multiclasses is achieved in mean square reconstruction error over one-stage image transform coding. Higher improvements are achieved with three stages. The reconstructed images with multistage coding are subjectively much more preferable than the reconstructed Images with one-stage coding.
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