V. Chande

Bio: V. Chande is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Variable-length code & Error detection and correction. The author has an hindex of 4, co-authored 7 publications receiving 335 citations.

Progressive transmission of images over memoryless noisy channels

Abstract: An embedded source code allows the decoder to reconstruct the source progressively from the prefixes of a single bit stream. It is desirable to design joint source-channel coding schemes which retain the capability of progressive reconstruction in the presence of channel noise or packet loss. Here, we address the problem of joint source-channel coding of images for progressive transmission over memoryless bit error or packet erasure channels. We develop a framework for encoding based on embedded source codes and embedded error correcting and error detecting channel codes. For a target transmission rate, we provide solutions and an algorithm for the design of optimal unequal error/erasure protection. Three performance measures are considered: the average distortion, the average peak signal-to-noise ratio, and the average useful source coding rate. Under the assumption of rate compatibility of the underlying channel codes, we provide necessary conditions for progressive transmission of joint source-channel codes. We also show that the unequal error/erasure protection policies that maximize the average useful source coding rate allow progressive transmission with optimal unequal protection at a number of intermediate rates.

Joint source-channel coding for progressive transmission of embedded source coders

Abstract: We present a scheme for joint source-channel coding for transmission of sources compressed by embedded source coders over a memoryless noisy channel. We find an exact solution to the problem of optimal channel code allocation. Then we investigate the properties of the solution which allow us to transmit the source progressively while retaining the optimality at intermediate and final transmission rates, using rate-compatible codes.

Image communication over noisy channels with feedback

Abstract: When a feedback channel is available from the receiver to the transmitter, adaptive schemes for source-channel coding can be used for image transmission. In this paper we see that the use of embedded source codes and embedded channel codes, when combined in a hybrid ARQ protocol, can provide the desired flexibility at high efficiency, low complexity and low feedback channel usage. We propose optimized schemes for transmission over Gilbert-Elliot channels, with and without constraints on the feedback channel usage. We observe that the end-to-end quality of the received image can be improved significantly by a moderate use of feedback.

A joint source-channel coding scheme for robust image transmission

Abstract: Summary form only given. We propose a joint source-channel coding scheme for the transmission of images over noisy channels. In this scheme, the interaction between source coding and channel coding is through a small number of parameters. A robust source coder based on the classification of the discrete wavelet transform (DWT) coefficients of the image is coupled with a flexible error control scheme which uses a bank of channel codes. Robustness in the source coder is achieved by scalar quantization of the coefficients followed by robust arithmetic coding to check catastrophic propagation of errors. Robust arithmetic coding generates a sequence of equal-length packets of bits along with a small number of sensitive bits for synchronization. A bank of rate compatible punctured convolutional codes concatenated with an outer error detection code like CRC is used for providing unequal error protection. Error detection is useful for error masking while decoding. The sensitive bits are protected and transmitted separately. An iterative algorithm is developed for selection of source coding rates and channel codes for the sequences of DWT coefficients. The algorithm uses the probabilities of packet decoding errors for the different channel codes and the operational rate distortion performance of the sequences of coefficients for the joint allocation. The system has a high reliability as the sensitive information is kept small. Some simulation results are provided for the transmission of the 512/spl times/512 image Lenna over binary symmetric channels.

A dynamic programming approach to constrained feedback hybrid ARQ design

Abstract: We address the problem of design of a hybrid ARQ system from a family of channel codes, so as to maximize the throughput for a given channel, subject to constraints on the feedback channel usage. We show that the problem can be modeled in a controlled Markov chain framework.

Rate-distortion optimized streaming of packetized media

Abstract: This paper addresses the problem of streaming packetized media over a lossy packet network in a rate-distortion optimized way. We show that although the data units in a media presentation generally depend on each other according to a directed acyclic graph, the problem of rate-distortion optimized streaming of an entire presentation can be reduced to the problem of error-cost optimized transmission of an isolated data unit. We show how to solve the latter problem in a variety of scenarios, including the important common scenario of sender-driven streaming with feedback over a best-effort network, which we couch in the framework of Markov decision processes. We derive a fast practical algorithm for nearly optimal streaming in this scenario, and we derive a general purpose iterative descent algorithm for locally optimal streaming in arbitrary scenarios. Experimental results show that systems based on our algorithms have steady-state gains of 2-6 dB or more over systems that are not rate-distortion optimized. Furthermore, our systems essentially achieve the best possible performance: the operational distortion-rate function of the source at the capacity of the packet erasure channel.

Unequal loss protection: graceful degradation of image quality over packet erasure channels through forward error correction

Abstract: We present the unequal loss protection (ULP) framework in which unequal amounts of forward error correction are applied to progressive data to provide graceful degradation of image quality as packet losses increase. We develop a simple algorithm that can find a good assignment within the ULP framework. We use the set partitioning in hierarchical trees coder in this work, but our algorithm can protect any progressive compression scheme. In addition, we promote the use of a PMF of expected channel conditions so that our system can work with almost any model or estimate of packet losses. We find that when optimizing for an exponential packet loss model with a mean loss rate of 20% and using a total rate of 0.2 bits per pixel on the Lenna image, good image quality can be obtained even when 40% of transmitted packets are lost.

Progressive transmission of images over memoryless noisy channels

Abstract: An embedded source code allows the decoder to reconstruct the source progressively from the prefixes of a single bit stream. It is desirable to design joint source-channel coding schemes which retain the capability of progressive reconstruction in the presence of channel noise or packet loss. Here, we address the problem of joint source-channel coding of images for progressive transmission over memoryless bit error or packet erasure channels. We develop a framework for encoding based on embedded source codes and embedded error correcting and error detecting channel codes. For a target transmission rate, we provide solutions and an algorithm for the design of optimal unequal error/erasure protection. Three performance measures are considered: the average distortion, the average peak signal-to-noise ratio, and the average useful source coding rate. Under the assumption of rate compatibility of the underlying channel codes, we provide necessary conditions for progressive transmission of joint source-channel codes. We also show that the unequal error/erasure protection policies that maximize the average useful source coding rate allow progressive transmission with optimal unequal protection at a number of intermediate rates.

Error-resilient image and video transmission over the Internet using unequal error protection

Abstract: This paper presents a new bit-plane-wise unequal error protection algorithm for progressive bitstreams transmitted over lossy networks. The proposed algorithm protects a compressed embedded bitstream generated by a 3-D SPIHT algorithm by assigning an unequal amount of forward error correction (FEC) to each bit-plane. The proposed algorithm reduces the amount of side information needed to send the size of each code to the decoder by limiting the number of quality levels to the number of bit-planes to be sent while providing a graceful degradation of picture quality as packet losses increase. We also apply our proposed algorithm to transmission of JPEG 2000 coded images over the Internet. To get additional error-resilience at high packet loss rates, we extend our algorithm to multiple-substream unequal error protection. Simulation results show that the proposed algorithm is simple, fast and robust in hostile network conditions and, therefore, can provide reasonable picture quality for video applications under varying network conditions.

Robust image transmission using JPEG2000 and turbo-codes

Abstract: A method of combined source and channel coding is described that provides robustness to errors from a binary symmetric channel and uses the JPEG2000 (JP2) image compression standard. The source code rate and channel code rate are jointly optimized to produce a stream of fixed-size channel packets, such that the rate allocation complexity grows O(N/sup 2/) with the number of transmitted packets, N. Punctured turbo codes are used for channel coding, providing strong error protection. The rate allocation scheme presented obtains all necessary information from the JP2 encoder, and does not require image decompression.