Robust image reconstruction enhancement based on Gaussian mixture model estimation

Fan Zhao; Jian Zhao; Xizhen Han; He Wang; Bochao Liu

doi:10.1117/1.JEI.25.2.023007

16 March 2016 Robust image reconstruction enhancement based on Gaussian mixture model estimation

Fan Zhao, Jian Zhao, Xizhen Han, He Wang, Bochao Liu

Author Affiliations +

Journal of Electronic Imaging, Vol. 25, Issue 2, 023007 (March 2016). https://doi.org/10.1117/1.JEI.25.2.023007

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.

Citation Download Citation

Fan Zhao, Jian Zhao, Xizhen Han, He Wang, and Bochao Liu "Robust image reconstruction enhancement based on Gaussian mixture model estimation," Journal of Electronic Imaging 25(2), 023007 (16 March 2016). https://doi.org/10.1117/1.JEI.25.2.023007

Published: 16 March 2016

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