Classification-Based Spatial Error Concealment for Visual Communications
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Classification-Based Spatial Error Concealment for Visual Communications Meng Chen, Yefeng Zheng, and Min Wu Department of Electrical and Computer Engineering, University of Maryland, College Park, MD 20742, USA Received 1 March 2005; Revised 11 August 2005; Accepted 22 August 2005 In an error-prone transmission environment, error concealment is an effective technique to reconstruct the damaged visual content. Due to large variations of image characteristics, different concealment approaches are necessary to accommodate the different nature of the lost image content. In this paper, we address this issue and propose using classification to integrate the state-of-theart error concealment techniques. The proposed approach takes advantage of multiple concealment algorithms and adaptively selects the suitable algorithm for each damaged image area. With growing awareness that the design of sender and receiver systems should be jointly considered for efficient and reliable multimedia communications, we proposed a set of classification-based block concealment schemes, including receiver-side classification, sender-side attachment, and sender-side embedding. Our experimental results provide extensive performance comparisons and demonstrate that the proposed classification-based error concealment approaches outperform the conventional approaches. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
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INTRODUCTION
Due to the various kinds of distortion and failures, part of a compressed image or video can be damaged or lost during transmission or storage. The widely used block-based visual coding systems have prompted a need of block-based error concealment on the decoder side. A number of concealment approaches have been proposed in recent years [1– 8]. The smoothness and continuity properties in spatial or frequency domain, the repeating patterns, and other properties of visual data have been exploited to recover corrupted blocks from the survived surroundings. Through a benchmarking effort on the existing error concealment approaches, we have observed that different approaches are suitable for different image characteristics of a corrupted block and its surroundings, and none of the existing approaches is an alltime champion. This motivates us to explore a classificationbased concealment approach that can combine the better performance of two state-of-the-art approaches in the literature. The classification-based approach also helps us achieve a better tradeoff between the concealment quality and the computation complexity on the receiver side. This is because some state-of-the-art approaches have rather high computation demand, and classification allows the computation power to be spent more strategically by performing expensive computations only when they are likely to offer a substantial gain in the concealment quality.
The classification in the proposed new framework of error concealment can be done either on the receiver side or on the sender side. The receiver-side classification uses the survived surroundi
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