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Image fuzzy enhancement algorithm based on contourlet transform domain

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Abstract

In order to solve the problems of low contrast, global darkness and noise amplification in some hyperspectral and remote-sensing images, a new image fuzzy enhancement method based on contourlet transform (CT) domain is proposed. The algorithm includes the following four steps. Firstly, the cyclic translation method is used to suppress the pseudo-Gibbs phenomenon caused by the lack of translation invariance of the CT. Secondly, a nonlinear gain function is designed to enhance and suppress the high-frequency coefficients adaptively. Meanwhile, the multi-scale Retinex with mixed gray function is used to process the low-frequency sub-band coefficients. Then, the inverse translation and linear averaging and the inverse CT are performed on the enhanced coefficients, and finally the improved fuzzy contrast is used to enhance the texture and edge of the image globally. The experimental results show that the proposed method can make the image texture details more prominent, and enhance the overall visual effect of the images. Furthermore, the absolute mean difference and PSNR of images are also greatly improved .

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Acknowledgments

The research work was jointly by grants from the National Key Research and the Development Plan Project (Grant no.2018YFB0104403) and National Natural Science Foundation of China (Grant no.71671044) .

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

    Yun-hu Huang & De-wang Chen

  2. Key laboratory of Intelligent Metro of Universities in Fujian Province, Fuzhou University, Fuzhou, China

    Yun-hu Huang & De-wang Chen

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  1. Yun-hu Huang
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  2. De-wang Chen
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Correspondence to Yun-hu Huang.

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Huang, Yh., Chen, Dw. Image fuzzy enhancement algorithm based on contourlet transform domain. Multimed Tools Appl 79, 35017–35032 (2020). https://doi.org/10.1007/s11042-019-08308-3

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