Efficient image compression based on side match vector quantization and digital inpainting View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-06-18

AUTHORS

Qing Zhou, Heng Yao, Fang Cao, Yu-Chen Hu

ABSTRACT

In this paper, we propose two efficient compression schemes for digital images using an adaptive selection mechanism for vector quantization (VQ), side match vector quantization (SMVQ), and image inpainting. On the sender side, after the original image is divided into blocks, the compression is implemented block by block. In both schemes, blocks in pre-specified locations are first compressed by VQ. For each remaining block, the optimal compression method (for the first scheme, including VQ or inpainting, and for the second scheme, including VQ, SMVQ, and inpainting) is determined by computing the mean square error (MSE) between the original block and its inpainted result and then comparing it with a predefined threshold. If MSE is greater than the threshold, image inpainting continues to be used to compress the current block. Otherwise, the compression mode of VQ or SMVQ is selected to substitute image inpainting to maintain higher visual quality. With the assistance of transmitted indicator flags, the receiver side can execute the image inpainting and decompression successfully. Experimental results demonstrate the effectiveness and superiority of two proposed schemes. More... »

PAGES

1-12

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11554-018-0800-1

DOI

http://dx.doi.org/10.1007/s11554-018-0800-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104906391


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