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Whats in the Image? Explorable Decoding of Compressed Images

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Document pages: 18 pages

Abstract: The ever-growing amounts of visual contents captured on a daily basisnecessitate the use of lossy compression methods in order to save storage spaceand transmission bandwidth. While extensive research efforts are devoted toimproving compression techniques, every method inevitably discards information.Especially at low bit rates, this information often corresponds to semanticallymeaningful visual cues, so that decompression involves significant ambiguity.In spite of this fact, existing decompression algorithms typically produce onlya single output, and do not allow the viewer to explore the set of images thatmap to the given compressed code. In this work we propose the first imagedecompression method to facilitate user-exploration of the diverse set ofnatural images that could have given rise to the compressed input code, thusgranting users the ability to determine what could and what could not have beenthere in the original scene. Specifically, we develop a novel deep-networkbased decoder architecture for the ubiquitous JPEG standard, which allowstraversing the set of decompressed images that are consistent with thecompressed JPEG file. To allow for simple user interaction, we develop agraphical user interface comprising several intuitive exploration tools,including an automatic tool for examining specific solutions of interest. Weexemplify our framework on graphical, medical and forensic use cases,demonstrating its wide range of potential applications.

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