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http://dx.doi.org/10.9717/kmms.2021.24.11.1461

A Light Exposure Correction Algorithm Using Binary Image Segmentation and Adaptive Fusion Weights  

Han, Kyu-Phil (Dept. of Computer Engineering, Kumoh National Institute of Technology)
Publication Information
Journal of Korea Multimedia Society / v.24, no.11, 2021 , pp. 1461-1471 More about this Journal
Abstract
This paper presents a light exposure correction algorithm for less pleasant images, acquired with a light metering failure. Since conventional tone mapping and gamma correction methods adopt a function mapping with the same range of input and output, the results are pleasurable for almost symmetric distributions to their intensity average. However, their corrections gave insufficient outputs for asymmetric cases at either bright or dark regions. Also, histogram modification approaches show good results on varied pattern images, but these generate unintentional noises at flat regions because of the compulsive shift of the intensity distribution. Therefore, in order to sufficient corrections for both bright and dark areas, the proposed algorithm calculates the gamma coefficients using primary parameters extracted from the global distribution. And the fusion weights are adaptively determined with complementary parameters, considering the classification information of a binary segmentation. As the result, the proposed algorithm can obtain a good output about both the symmetric and the asymmetric distribution images even with severe exposure values.
Keywords
Exposure correction; Light metering; Image segmentation; Exposure fusion; Gamma correction;
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