Image enhancement based on intrascale dependencies of the second generation curvelet transform

Hongxia Hao; Fang Liu; Licheng Jiao

doi:10.1117/12.832501

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30 October 2009 Image enhancement based on intrascale dependencies of the second generation curvelet transform

Hongxia Hao, Fang Liu, Licheng Jiao

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Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 749849 (2009) https://doi.org/10.1117/12.832501
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

This paper presents a strong noise image enhancement method based on intrascale dependencies of the second generation curvelet transform. Observing that the immediate four neighbor coefficients bear the most important dependencies, we use spatial clustering property of the intrascale neighbor coefficients to separate noise and signal of interest, and to deal with them differently, i.e. to suppress noise and strengthen edges. Comparing our approach with Starck's enhancement model (Starck et al., 2003), we experimentally find that for high noise level images, our method outperforms the starck's system in noise suppression and signal strengthening and produces better enhancement results.

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Hongxia Hao, Fang Liu, and Licheng Jiao "Image enhancement based on intrascale dependencies of the second generation curvelet transform", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 749849 (30 October 2009); https://doi.org/10.1117/12.832501

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