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The Rate-Distortion-Accuracy Tradeoff JPEG Case Study

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Document pages: 17 pages

Abstract: Handling digital images is almost always accompanied by a lossy compressionin order to facilitate efficient transmission and storage. This introduces anunavoidable tension between the allocated bit-budget (rate) and thefaithfulness of the resulting image to the original one (distortion). Anadditional complicating consideration is the effect of the compression onrecognition performance by given classifiers (accuracy). This work aims toexplore this rate-distortion-accuracy tradeoff. As a case study, we focus onthe design of the quantization tables in the JPEG compression standard. Weoffer a novel optimal tuning of these tables via continuous optimization,leveraging a differential implementation of both the JPEG encoder-decoder andan entropy estimator. This enables us to offer a unified framework thatconsiders the interplay between rate, distortion and classification accuracy.In all these fronts, we report a substantial boost in performance by a simpleand easily implemented modification of these tables.

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