J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. Commun., vol. 29, pp. 1261-1273, Sept. 1981.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....toward the joint design of source and channel coders. A class of joint source channel coders are designed by attempting to optimally allocate a fixed bitrate between the source and channel coders to achieve the maximum overall system performance. Examples of the works in this class are present in [2] [6] The applications span across the areas of speech, image and video coding such as that of Modestino et al. on image coding using the discrete cosine transform with convolutional channel coding [2] the work of Moore and Gibson on DPCM speech coding with self orthogonal convolutional coding ....

....the maximum overall system performance. Examples of the works in this class are present in [2] 6] The applications span across the areas of speech, image and video coding such as that of Modestino et al. on image coding using the discrete cosine transform with convolutional channel coding [2], the work of Moore and Gibson on DPCM speech coding with self orthogonal convolutional coding [3] and the work of Bystrom and Modestino on combined source channel coding for video transmission [4] Other methods of joint source and channel coding include the systems designed based on Unequal ....

J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined source channel coding of images using the block cosine transform," IEEE Trans. Commun., vol. COM-29, pp. 1262-1274, Sept. 1981.

.... studied the transmission of PCM data over a noisy channel, ignoring the code signment problem [3] Rydbeck and Sundberg, without considering the quantizer design problem, have shown that the code assignmen plays an important role in de termining the system performance [4] References [5] and [6] consider the problem of combined source channel coding for the transmission of still images. In [7] Far vatdin and Vaishampayan provide an algorithm for minimizing total distortion caused by the quantization and channel noise. Later, the same researchers present method for the joint ....

J.W.Modestino, D.G.Daut and A.L.Vickers, "Combined Source-Channel Coding of Images Using the Block Cosine Transform", IEEE Transactions on Communications, vol. COM-29, No. 9, pp. 1261-1274, September 1981.

....IS 95) The bit allocation problem of the quantizer array is solved by using a new approach based on the integer programming technique. Without bandwidth expansion, our proposed scheme results in an improvement in the reconstructed image quality, especially for good channel conditions. References [2] consider the problem of combined source channel coding for the transmission of still images. In [3] Farvardin and Vaishampayan provide an algorithm for minimizing total distortion caused by the quantization and channel noise. Later, the same researchers present a method for the joint ....

J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined sourcechannel coding of images using the block cosine transform," IEEE Trans. Commun., vol. COM-29, pp. 1261--1274, Sept. 1981.

....and concealment options with particular emphasis on wireless video applications. 2.1 Data partitioning and layered coding Scalable and joint source channel coding are important ways for providing real time transport. Very early evidence of combined source channel coding technique exists in [28] which discusses its usage for images. More recently, works presented in [8,22,35] discussed the usage of such techniques for real time services. Particular emphasis is given to scalable coding for VBR video over ATM networks in [9,12] Data loss is a major problem for transmitting video over ....

J.W. Modestino, D.G. Daut, and A.L. Vickers. Combined source-channel coding of images using the block cosine transform. IEEE Transactions on Communications, COM-29(9), September 1981.

....Therefore, it is desirable for an image coding scheme to have good balance between compression and error resilience by organizing encoded bitstream in such a way that it is less sensitive to the channel noise. Various approaches for image transmission through noisy channels have been proposed [1,6,8,9,11,13], using either explicit error correction coding, error concealment without modi cation to the encoder, or custom designed error resilient encoder decoder pairs. Modestino et al. proposed a coding scheme [8] that considers the DCT parameters, channel coding and modulation. The reconstructed image ....

....approaches for image transmission through noisy channels have been proposed [1,6,8,9,11,13] using either explicit error correction coding, error concealment without modi cation to the encoder, or custom designed error resilient encoder decoder pairs. Modestino et al. proposed a coding scheme [8] that considers the DCT parameters, channel coding and modulation. The reconstructed image quality has been improved signi cantly by trading quantization accuracy for error control protection through explicit channel coding. Vaishampayan and Farvardin [13] presented an optimal joint source channel ....

J.W. Modestino, D.G. Daut, A.L. Vickers, Combined source-channel coding of images using the block cosine transform, IEEE Trans. Commun. COM-29 (1981) 1261}1274.

....By providing error control protection to those encoded bits that contribute most significantly to image reconstruction, it was possible to minimize the degradation caused by channel errors without sacrificing transmission bandwidth. They extended this method to block transform image coding in [14]. Since Hagenauer [15] introduced an application of ratecompatible punctured convolutional codes (RCPC) to unequal error protection, many 4 researchers have used RCPC codes to provide unequal error protection. RCPC codes allow convolutional codes of several different rates to be used with only ....

J. W. Modestino ,D. G. Daut and A. L. Vickers, " Combined source-channel coding of images using the block cosine transform," IEEE Trans. Commun., vol. COM-29, pp. 1261-1274, 1981

....options of multimedia compression schemes can be easily adapted, controlled by channel quality in order to achieve a better overall performance. Combined and joint source and channel coding has been previously investigated for still images by Modestino et al. as early as 1979 in [2] and in [3], 4] For some Markov sources, Farvardin et al. give optimal quantizers for noisy channels [5] and discuss vector quantization for noisy channels [6] Gray et al. designed joint source and channel trellis waveform coders [7] For speech transmission on mobile channels design examples and further ....

J. W. Modestino, D. G. Daut and A. L. Vickers, \Combined Source-Channel Coding of Images Using the Block Cosine Transform," IEEE Transactions on Communications, vol. COM-29, pp. 1261-1274, Sept. 1981.

....schemes and concealment options with particular emphasis on wireless video applications. 2.1 Data partitioning and layered coding Scalable and joint source channel coding important ways for providing real time transport. Very early evidence of combined source channel coding technique exists in [24] which discusses its usage for images. More recently, works presented in [7,18,31] discussed the usage of such techniques for real time services. Particular emphasis is given to scalable coding for VBR video over ATM networks in [8,11] Data loss is a major problem for transmitting video over ....

J.W. Modestino, D.G. Daut, and A.L. Vickers. Combined source-channel coding of images using the block cosine transform. IEEE Transactions on Communications, COM-29(9), September 1981.

....schemes in video communications must be based of prudent decisions because video transmissions are already very bandwidth intensive. Joint source channel coding (JSCC) schemes minimize transmission errors by designing jointly quantizers and channel coders, according to a given channel error model [16, 42, 43, 70]. To cope with noisy channels, they try to optimally partition bandwidth between the source and channel coders, depending on channel loss status, normally characterized by some parameters. They are, however, hard to apply in the Internet since the Internet does not have a well defined channel ....

J. W. Modestino, D. G. Daut, and A. L. Vickers. Combined source-channel coding of images using the block cosine transform. IEEE Trans. on Communications, COM29: 1261-1273, Sept. 1981.

....probability, and can be used as such for further processing. We also show some possible applications in joint sourcechannel coding schemes. 1 INTRODUCTION The eld of joint source channel coding (JSCC) has been studied in many di erent ways up to now and has lead to numerous di erent techniques [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]. One of the problems of the joint study of source and channel codes is to obtain a coherent quality measure for these two coders. Many systems rely on the knowledge of a bit or symbol error probability of the channel but fail to take into account the presence of an error correcting code. We ....

James W. Modestino, David G. Daut, and Acie L. Vickers. Combined source-channel coding of images using the block cosine transform. IEEE Transactions on Communications, 29(9):1261-1274, September 1981.

....options of multimedia compression schemes can be easily adapted, controlled by channel quality in order to achieve a better overall performance. Combined and joint source and channel coding has been previously investigated for still images by Modestino et al. as early as 1979 in [2] and in [3], 4] For some Markov sources, Farvardin et al. give optimal quantizers for noisy channels [5] and discuss vector quantization for noisy channels [6] Gray et al. designed joint source and channel trellis waveform coders [7] For speech transmission on mobile channels design examples and further ....

J. W. Modestino, D. G. Daut and A. L. Vickers, \Combined Source-Channel Coding of Images Using the Block Cosine Transform," IEEE Transactions on Communications, vol. COM-29, pp. 1261-1274, Sept. 1981.

....such systems. In a typical system using subband or transform coding, the source is modeled as a finite collection of classes S j of continuous valued random variables (r.v.s) where each class contains r.v.s with the same density function, and corresponds to a particular frequency band. In [4], the three most commonly used unequal error protection schemes for channel coding the quantizer output indices for each class are listed: Type 1 uses the same channel coding rate for each quantizer index across all classes; Type 2 uses different channel coding rates r j for the different classes ....

....Type 2 uses different channel coding rates r j for the different classes S j , and Type 3 uses different channel coding rates r j;k for the kth bit of each quantizer index in class S j . The results in this paper apply to systems using Type 1 or Type 2 error protection, such as those considered in [3, 4, 6]. To compute the end to end distortion without measuring or bounding the p(jji) all of the papers [3] 7] assume errors in the the bits of the received n bit index j to be independent, 2 and (in the case of Type 1 or Type 2 systems only) identically distributed (i.i.d. With the independence ....

J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. on Communications, vol. 29, no. 9, pp. 1261-1274, Sep. 1981.

....The goal then is to make sure that the more important bands are received without error or loss at the destinations. One way to do this in the current single class best effort service Internet is to use FEC schemes to provide unequal error protection proportional to the importance of each band [33, 48, 1]. This amounts in practice to allocating more FEC information to these bands. The problem then is that of a bit allocation problem: how many bits of main and redundant information should be allocated to each band given a model for the network and a distorsion function that takes into account the ....

J. W. Modestino et al., "Combined source-channel coding of images using the block cosine transform", IEEE Trans. Comm., vol. 29, pp. 1261-1274, Sept. 1981.

....channel coding. Shannon s source channel separation theorem [1, 2] shows that a source code and a channel code can be designed separately and used in tandem without loss of optimality. However, in the presence of delay complexity constraints, joint source channel coding outperforms tandem coding [3, 4, 5] and minimizes the transmission bandwidth [6, 7] In many practical situations, delay constraints as well as imperfect knowledge about the source statistics result in a suboptimal source coder. This suboptimality is reflected in the fact that the source encoder does not eliminate all the ....

J. Modestino, D. Daut, and A. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. Commun., vol. 29, pp. 1262--1274, Sep. 1981.

....bits between the source and channel coders to minimize total distortion, while satisfying a constraint on the total rate. Several approaches for joint source channel coding have been proposed in the literature. Modestino et. al illustrated the advantages of source channel coding using the DCT in [1] extending their earlier work using DPCM coding. Joint source channel coding of synthetic sources using vector quantization combined with Rate Compatible Punctured Convolutional codes is addressed in [2] A joint source channel decoding approach in the form of MAP decoding for exploiting residual ....

J.W.Modestino, D.G.Daut and A.L.Vickers, "Combined Source-Channel Coding of Images Using the Block Cosine Transform," IEEE Transactions on Communications, Vol.29, pp.1261-1274, Sep. 1981,.

....21] The goal then is to make sure that the more important bands are received without error or loss at the destinations. One way to do this in the current single class best effort service Internet is to use FEC schemes to provide unequal error protection proportional to the importance of each band [27, 40]. This amounts in practice to allocating more FEC information to these bands. The problem then is that of a bit allocation problem: how many bits of main and redundant information should be allocated to each band given a model for the network and a distorsion function that takes into account the ....

J. W. Modestino et al., "Combined source-channel coding of images using the block cosine transform", IEEE Trans. Comm., vol. 29, pp. 1261-1274, Sept. 1981.

....subject to a constraint on the overall coding rate. Several constructive approaches for combined source channel coding have been proposed in the literature. One of the earliest papers in this area is by Modestino et al. who illustrate the advantages of source channel coding using the DCT in [2]. Vaishampayan and Farvardin [3] present a source channel DCT coding approach using quantizers optimized for noisy channels. They also provide theoretical predictions for performance and rate distortion theoretic bounds based on an image model. There has been a large body of work on robust vector ....

J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Transactions on Communications, vol. 29, no. 9, pp. 1261--1274, September 1981.

....necessary either when the CSNR is very low, as e.g. in many satellite channels, or when the signal parameter dynamics are large, like in audio signals, the problem is more difficult. Several authors have addressed this kind of problem for the combination of vector quantization and binary channels [1, 10, 19, 20]. We believe that combination of the two types of results need to be utilized for flexible implementations of future wireless communication systems 1 . ....

J. W. Modestino, D. G. Daut, and Vickers. Combined source--channel coding of images using the block cosine transform. IEEE Trans. Commun., COM--29:1262--1274, September 1981.

....in the channel distortion model. In addition, it provides a framework which could be extended to allow analysis and joint minimization of the source and channel induced distortion in an end to end system. Some of the earliest work in joint source channel coding was performed by Daut and Modestino [2], who combined performance bounds on error correcting codes and basic quantizer theory to explore the optimal allocation of a fixed number of bits to source and channel coding. One of the results in the present paper is closely related to the channel distortion formula given in [2] though we ....

....and Modestino [2] who combined performance bounds on error correcting codes and basic quantizer theory to explore the optimal allocation of a fixed number of bits to source and channel coding. One of the results in the present paper is closely related to the channel distortion formula given in [2], though we are using block codes and consider distortion in run length, entropy coded data, while the work in [2] uses convolutional codes and fixed length data representations. Any treatment of the joint source channel problem raises the issue of the relationship between channel errors and the ....

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J. W. Modestino, D. G. Daut, A. L. Vickers, "Combined Source-Channel Coding of Images Using the Block Cosine Transform," IEEE Trans. on Communications, Vol. Com-29, No. 9, pp. 1261-1274, September 1981.

....theory, appears too inefficient in practice given the demanding requirements on bit rate, complexity, delay, and of robustness to noisy time varying channels. Thus, several researchers have been investigating the applicability of combined source channel coding to robust image compression [1] [2], 3] A major shortcoming of the standard source channel image coding techniques is due to their use of fixed length encoding. It is well known that as long as vector dimensions are not excessively high, fixed length source coders are significantly inferior to variable length coders in terms of ....

....channel errors that may cause desynchronization and catastrophic error propagation. Fixed length coding offers greater robustness to channel errors, as an error is confined to just one codeword. Indeed, image coders for noisy channel environments predominantly use fixed length coding (e.g. 1] [2] , 3] and compression performance is sacrificed for error resilience. Ideally, we would like to achieve the best of both worlds, namely, robustness to channel errors and high compression efficiency. In this paper, we propose a method to optimize the tradeoff between the two competing objectives ....

[Article contains additional citation context not shown here]

J. W. Modestino, D. G. Daut and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. on Com., vol. 29, pp. 1261-74, Sep. 1981.

....a single bit in a compressed image can result in catastrophic loss of synchronization during decoding. The problem of channel error propagation and the resulting degradation in image quality has been studied in the context of zero memory quantizers [4] predictive coding [8] transform coding [12, 9] and subband coding [11] The above papers adopt the approach of combining source coding and forward error correction (FEC) techniques in an attempt to minimize the mean square error of the reconstructed image. In this paper, we introduce a combined source channel coding approach that uses error ....

J. Modestino, D. Daut, and A. Vickers. "Combined source-channel coding of images using the block cosine transform". IEEE Transactions on Communications, Com-29:1261--1274, September 1981.

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J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. Commun., vol. 29, pp. 1261-1273, Sept. 1981.

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J.W. Modestino, D.G. Daut and A.L. Vickers, "Combined Source-Channel Coding of Images Using the Block Cosine Transform, " IEEE Trans. Commun., vol. COM-29, pp. 1261--1274, Sept. 1981.

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J. W. Modestino, D. G. Daut and A. L. Vickers, "Combined source-channel coding of images using the block cosine transform," IEEE Trans. Comm., vol. COM-29, pp. 1261-1274, 1981.

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J. W. Modestino, D. G. Daut, and A. L. Vickers, "Combined sourcechannel coding of images using the block cosine transform," IEEE Trans. Commun., vol. COM-29, pp. 1261--1274, Sept. 1981.

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