Enhancing sparse representation of color images by cross channel transformation

被引:1
|
作者
Rebollo-Neira, Laura [1 ]
Inacio, Aurelien [2 ]
机构
[1] Aston Univ, Math Dept, Birmingham B4 7ET, England
[2] ENSIIE, Paris, France
来源
PLOS ONE | 2023年 / 18卷 / 01期
关键词
FACE RECOGNITION; SUPERRESOLUTION; SAMPLES;
D O I
10.1371/journal.pone.0279917
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Transformations for enhancing sparsity in the approximation of color images by 2D atomic decomposition are discussed. The sparsity is firstly considered with respect to the most significant coefficients in the wavelet decomposition of the color image. The discrete cosine transform is singled out as an effective 3 point transformation for this purpose. The enhanced feature is further exploited by approximating the transformed arrays using an effective greedy strategy with a separable highly redundant dictionary. The relevance of the achieved sparsity is illustrated by a simple encoding procedure. On typical test images the compression at high quality recovery is shown to significantly improve upon JPEG and WebP formats.
引用
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页数:17
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