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Optimized-SSIM Based Quantization in Optical Remote Sensing Image Compression

Authors: Kai Yang; Hongxu Jiang;

Optimized-SSIM Based Quantization in Optical Remote Sensing Image Compression

Abstract

High-rate compression usually causes serious distortion of texture and edges which play important roles in optical remote sensing image application. In order to reduce obvious structural distortion, in this paper, we analyze the correlation of SSIM (Structural Similarity) component functions with MOS (Mean Opinion Score) on an optical remote sensing compression distortion image database, conclude that SSIM should be substituted by its component function in optical remote sensing image compression assessment. After that, we utilize the component function to design a quantization approach, and apply it to an embedded wavelet image coder. Experiments show that our approach can preserve more structure and texture in image by high-rate compression.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Average
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