This paper proposes a cloud-based distributed image coding scheme (Cloud-DIC) to exploit the strong correlations with external partial-duplicate images in the cloud. It features both high coding efficiency and low encoder complexity, which makes it suitable for photo sharing on mobile devices. To get the side information in the cloud, a thumbnail of the current image is transmitted to retrieve highly correlated images and reconstruct through geometrical registration and adaptive patched-based stitching. The current image is then compressed by a transform-domain syndrome coding, bitplane by bitplane. Once a bitplane is received, the decoded high-quality image is further used to refine the side information in the cloud, which will benefit the coding of following bitplanes and the reconstruction. Experimental results on a landmark image database show that it can largely enhance the coding efficiency both subjectively and objectively with up to 5 dB gains and 58% bits saving over JPEG.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper proposes a cloud-based distributed image coding scheme (Cloud-DIC) to exploit the strong correlations with external partial-duplicate images in the cloud. It features both high coding efficiency and low encoder complexity, which makes it suitable for photo sharing on mobile devices. To get the side information in the cloud, a thumbnail of the current 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