# Automatic Exposure Compensation for Multi-Exposure Image Fusion

arXiv: https://arxiv.org/abs/1805.11211 · HTML: https://mlsanity.com/paper/1805.11211/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 May 2018.

## Built on by (most cited first, 2 of 2)

- [Examining Autoexposure for Challenging Scenes](https://mlsanity.com/paper/2309.04542/) (2023)
- [AutoLumNet: Monotone Optimal Transport for Single-Shot Exposure Correction](https://mlsanity.com/paper/2608.19860/) (2026)

## Abstract (arXiv)

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.