With multimedia flourishing on the Web, it is easy to find similar images for a query, especially landmark images. Traditional image coding, such as JPEG, cannot exploit correlations with external images. Existing vis...
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With multimedia flourishing on the Web, it is easy to find similar images for a query, especially landmark images. Traditional image coding, such as JPEG, cannot exploit correlations with external images. Existing vision-based approaches are able to exploit such correlations by reconstructing from local descriptors but cannot ensure the pixel-level fidelity of the reconstruction. In this paper, a cloud-based distributed image coding (cloud-DIC) scheme is proposed to exploit external correlations for mobile photo uploading. For each input image, a thumbnail is transmitted to retrieve correlated images and reconstruct it in the cloud by geometrical and illumination registrations. Such a reconstruction serves as the side information (SI) in the cloud-DIC. The image is then compressed by a transform-domain syndrome coding to correct the disparity between the original image and the SI. Once a bitplane is received in the cloud, an iterative refinement process is performed between the final reconstruction and the SI. Moreover, a joint encoder/decoder mode decision at block, frequency, and bitplane levels is proposed to adapt to different correlations. Experimental results on a landmark image database show that the cloud-DIC can largely enhance the coding efficiency both subjectively and objectively, with up to 5-dB gains and 70% bits saving over JPEG with arithmetic coding, and perform comparably at low bitrates with the intra coding of the High Efficiency Video coding standard with a much lower encoder complexity.
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 enc...
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ISBN:
(纸本)9781479957521
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 bit-planes 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.
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