NDLI: Adaptive Remote Sensing Texture Compression on GPU

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Adaptive Remote Sensing Texture Compression on GPU

Content Provider	Semantic Scholar
Author	Lu, Xiao-Xia Li, Sikun
Copyright Year	2010
Abstract	Considering the properties of remote sensing texture such as strong randomness and weak local correlation, a novel adaptive compression method based on vector quantizer is presented and implemented on GPU. Utilizing the property of Human Visual System (HVS), a new similarity measurement function is designed instead of using Euclid distance. Correlated threshold between blocks can be obtained adaptively according to the property of different images without artificial auxiliary. Furthermore, a self-adaptive threshold adjustment during the compression is designed to improve the reconstruct quality. Experiments show that the method can handle various resolution images adaptively. It can achieve satisfied compression rate and reconstruct quality at the same time. Index is coded to further increase the compression rate. The coding way is designed to guarantee accessing the index randomly too. Furthermore, the compression and decompression process is speed up with the usage of GPU, on account of their parallelism.
Starting Page	46
Ending Page	52
Page Count	7
File Format	PDF HTM / HTML
DOI	10.5815/ijigsp.2010.01.06
Volume Number	2
Alternate Webpage(s)	http://www.mecs-press.org/ijigsp/ijigsp-v2-n1/IJIGSP-V2-N1-6.pdf
Alternate Webpage(s)	https://doi.org/10.5815/ijigsp.2010.01.06
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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