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Remote Sens. 2019, 11(7), 849;

Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification

School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Author to whom correspondence should be addressed.
Received: 14 March 2019 / Revised: 3 April 2019 / Accepted: 4 April 2019 / Published: 8 April 2019
(This article belongs to the Section Remote Sensing Image Processing)
PDF [7900 KB, uploaded 12 April 2019]


In this paper, an optimized contrast enhancement method combining global and local enhancement results is proposed to improve the visual quality of infrared images. Global and local contrast enhancement methods have their merits and demerits, respectively. The proposed method utilizes the complementary characteristics of these two methods to achieve noticeable contrast enhancement without artifacts. In our proposed method, the 2D histogram, which contains both global and local gray level distribution characteristics of the original image, is computed first. Then, based on the 2D histogram, the global and local enhanced results are obtained by applying histogram specification globally and locally. Lastly, the enhanced result is computed by solving an optimization equation subjected to global and local constraints. The pixel-wise regularization parameters for the optimization equation are adaptively determined based on the edge information of the original image. Thus, the proposed method is able to enhance the local contrast while preserving the naturalness of the original image. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms the block-based methods for improving the visual quality of infrared images. View Full-Text
Keywords: 2D histogram; histogram specification; optimization equation; contrast enhancement 2D histogram; histogram specification; optimization equation; contrast enhancement

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Liu, C.; Sui, X.; Kuang, X.; Liu, Y.; Gu, G.; Chen, Q. Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification. Remote Sens. 2019, 11, 849.

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