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- W2022797032 abstract "A novel theory of information acquisition-compressive sampling has been applied in this paper, and goes against the common wisdom in data acquisition of Shannon theorem. CS theory asserts that one can recover certain signals and images perfectly from far fewer samples or measurements than traditional methods use. This paper presents an improvement on genetic algorithm instead of match pursuit algorithm in consideration of the enormous computational complexity on sparse decomposition. Then the whole image is divided into small blocks which can be processed by sparse decomposition, and an end to decomposition is determined by PSNR threshold adaptively. At last, the experiment results show that good performance on image reconstruction with less computational complexity has been achieved." @default.
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- W2022797032 date "2009-08-20" @default.
- W2022797032 modified "2023-09-22" @default.
- W2022797032 title "<title>Hyperspectral image reconstruction based on an improved genetic algorithm</title>" @default.
- W2022797032 doi "https://doi.org/10.1117/12.825603" @default.
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