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Robust image reconstruction enhancement based on Gaussian mixture model estimation

[+] Author Affiliations
Fan Zhao

Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics, No. 88 Yingkou Street, Erdao District, Changchun 130033, China

University of Chinese Academy of Sciences, No. 19 Yuquan Street, Shijingshan District, Beijing 100049, China

Jian Zhao, Xizhen Han, He Wang, Bochao Liu

Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics, No. 88 Yingkou Street, Erdao District, Changchun 130033, China

J. Electron. Imaging. 25(2), 023007 (Mar 16, 2016). doi:10.1117/1.JEI.25.2.023007
History: Received September 14, 2015; Accepted February 9, 2016
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Abstract.  The low quality of an image is often characterized by low contrast and blurred edge details. Gradients have a direct relationship with image edge details. More specifically, the larger the gradients, the clearer the image details become. Robust image reconstruction enhancement based on Gaussian mixture model estimation is proposed here. First, image is transformed to its gradient domain, obtaining the gradient histogram. Second, the gradient histogram is estimated and extended using a Gaussian mixture model, and the predetermined function is constructed. Then, using histogram specification technology, the gradient field is enhanced with the constraint of the predetermined function. Finally, a matrix sine transform-based method is applied to reconstruct the enhanced image from the enhanced gradient field. Experimental results show that the proposed algorithm can effectively enhance different types of images such as medical image, aerial image, and visible image, providing high-quality image information for high-level processing.

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Citation

Fan Zhao ; Jian Zhao ; Xizhen Han ; He Wang and Bochao Liu
"Robust image reconstruction enhancement based on Gaussian mixture model estimation", J. Electron. Imaging. 25(2), 023007 (Mar 16, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.2.023007


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