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JBE, vol. 22, no. 6, pp.702-712, November, 2017

DOI: https://doi.org/10.5909/JBE.2017.22.6.702

Patch based Multi-Exposure Image Fusion using Unsharp Masking and Gamma Transformation

Jihwan Kim, Hyunho Choi, and Jechang Jeong

C.A E-mail: jjeong@hanyang.ac.kr

Abstract:

In this paper, we propose an unsharp masking algorithm using Laplacian as a weight map for the signal structure and a gamma transformation algorithm using image mean intensity as a weight map for mean intensity. The conventional weight map based on the patch has a disadvantage in that the brightness in the image is shifted to one side in the signal structure and the mean intensity region. So the detailed information is lost. In this paper, we improved the detail using unsharp masking of patch unit and proposed linearly combined the gamma transformed values using the average brightness values of the global and local images. Through the proposed algorithm, the detail information such as edges are preserved and the subjective image quality is improved by adjusting the brightness of the light. Experiment results show that the proposed algorithm show better performance than conventional algorithm.



Keyword: Multi-Exposure Image Fusion, High Dynamic Range, Gamma Transformation, Unsharp Masking, Edge enhancement

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