TitleA new image contrast enhancement algorithm using exposure fusion framework
AuthorsYing, Zhenqiang
Li, Ge
Ren, Yurui
Wang, Ronggang
Wang, Wenmin
AffiliationSchool of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, China
Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
Issue Date2017
Publisher17th International Conference on Computer Analysis of Images and Patterns, CAIP 2017
Citation17th International Conference on Computer Analysis of Images and Patterns, CAIP 2017. 2017, 10425 LNCS, 36-46.
AbstractLow-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. ? Springer International Publishing AG 2017.
URIhttp://hdl.handle.net/20.500.11897/505195
ISSN9783319646978
DOI10.1007/978-3-319-64698-5_4
IndexedEI
Appears in Collections:信息工程学院

Files in This Work
There are no files associated with this item.

Web of Science®



Checked on Last Week

Scopus®



Checked on Current Time

百度学术™



Checked on Current Time

Google Scholar™





License: See PKU IR operational policies.