English

Automatic Exposure Compensation for Multi-Exposure Image Fusion

Computer Vision and Pattern Recognition 2018-05-30 v1

Abstract

This paper proposes a novel luminance adjustment method based on automatic exposure compensation for multi-exposure image fusion. Multi-exposure image fusion is a method to produce images without saturation regions, by using photos with different exposures. In conventional works, it has been pointed out that the quality of those multi-exposure images can be improved by adjusting the luminance of them. However, how to determine the degree of adjustment has never been discussed. This paper therefore proposes a way to automatically determines the degree on the basis of the luminance distribution of input multi-exposure images. Moreover, new weights, called "simple weights", for image fusion are also considered for the proposed luminance adjustment method. Experimental results show that the multi-exposure images adjusted by the proposed method have better quality than the input multi-exposure ones in terms of the well-exposedness. It is also confirmed that the proposed simple weights provide the highest score of statistical naturalness and discrete entropy in all fusion methods.

Keywords

Cite

@article{arxiv.1805.11211,
  title  = {Automatic Exposure Compensation for Multi-Exposure Image Fusion},
  author = {Yuma Kinoshita and Sayaka Shiota and Hitoshi Kiya},
  journal= {arXiv preprint arXiv:1805.11211},
  year   = {2018}
}

Comments

To appear in Proc. ICIP2018 October 07-10, 2018, Athens, Greece

R2 v1 2026-06-23T02:11:17.550Z