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A New Image Contrast Enhancement Algorithm Using Exposure Fusion Framework

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10425)

Abstract

Low-light images are not conducive to human observation and computer vision algorithms due to their low visibility. Although many image enhancement techniques have been proposed to solve this problem, existing methods inevitably introduce contrast under- and over-enhancement. In this paper, we propose an image contrast enhancement algorithm to provide an accurate contrast enhancement. Specifically, we first design the weight matrix for image fusion using illumination estimation techniques. Then we introduce our camera response model to synthesize multi-exposure images. Next, we find the best exposure ratio so that the synthetic image is well-exposed in the regions where the original image under-exposed. Finally, the input image and the synthetic image are fused according to the weight matrix to obtain the enhancement result. Experiments show that our method can obtain results with less contrast and lightness distortion compared to that of several state-of-the-art methods.

Keywords

Image enhancement Contrast enhancement Exposure compensation Exposure fusion 

Notes

Acknowledgments

This work was supported by the grant of National Science Foundation of China (No.U1611461), Shenzhen Peacock Plan (20130408-183003656), and Science and Technology Planning Project of Guangdong Province, China (No. 2014B090910001 and No. 2014B010117007).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Electronic and Computer EngineeringShenzhen Graduate School, Peking UniversityShenzhenChina
  2. 2.Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianChina

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