CVAug 1, 2018

A Pseudo Multi-Exposure Fusion Method Using Single Image

arXiv:1808.00195v18 citations
Originality Incremental advance
AI Analysis

This addresses a domain-specific problem for image processing applications, offering an incremental improvement by enabling multi-exposure fusion from single images.

The paper tackles the problem of generating multi-exposure images from a single input, which is needed for dynamic scenes or existing media where capturing multiple exposures is impractical, and shows effectiveness through experimental comparisons with conventional methods.

This paper proposes a novel pseudo multi-exposure image fusion method based on a single image. Multi-exposure image fusion is used to produce images without saturation regions, by using photos with different exposures. However, it is difficult to take photos suited for the multi-exposure image fusion when we take a photo of dynamic scenes or record a video. In addition, the multi-exposure image fusion cannot be applied to existing images with a single exposure or videos. The proposed method enables us to produce pseudo multi-exposure images from a single image. To produce multi-exposure images, the proposed method utilizes the relationship between the exposure values and pixel values, which is obtained by assuming that a digital camera has a linear response function. Moreover, it is shown that the use of a local contrast enhancement method allows us to produce pseudo multi-exposure images with higher quality. Most of conventional multi-exposure image fusion methods are also applicable to the proposed multi-exposure images. Experimental results show the effectiveness of the proposed method by comparing the proposed one with conventional ones.

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