Multi-exposure Image Fusion Method Using Anisotropic Diffusion

Bhateja, Vikrant; Singhal, Ashutosh; Singh, Anil Kumar

doi:10.1007/978-981-13-1165-9_80

Cited by 3 publications

(2 citation statements)

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“…Image fusion is a process in image synthesis where various source images obtained from multiple sources of the same object/scene are combined to produce synthetic and visually improved images for human visual perception [1]. With the continuous improvement of the camera functions of mobile devices, such as mobile phones, photography is becoming more and more convenient and fast, and the content and performance of images are constantly enriched, making people invariably pursue technological perfection.…”

Section: Introductionmentioning

confidence: 99%

Information-Theoretic Channel for Multi-exposure Image Fusion

Hao

Zhao

Sbert

et al. 2021

The Computer Journal

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Multi-exposure image fusion has emerged as an increasingly important and interesting research topic in information fusion. It aims at producing an image with high quality by fusing a set of differently exposed images. In this article, we present a pixel-level method for multi-exposure image fusion based on an information-theoretic approach. In our scheme, an information channel between two source images is used to compute the Rényi entropy associated with each pixel in one image with respect to the other image and hence to produce the weight maps for the source images. Since direct weight-averaging of the source images introduce unpleasing artifacts, we employ Laplacian multi-scale fusion. Based on this pyramid scheme, images at every scale are fused by weight maps, and a final fused image is inversely reconstructed. Multi-exposure image fusion with the proposed method is easy to construct and implement and can deliver, in less than a second for a set of three input images of size 512$\times $340, competitive and compelling results versus state-of-art methods through visual comparison and objective evaluation.

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Section: Introductionmentioning

confidence: 99%

Information-Theoretic Channel for Multi-exposure Image Fusion

Hao

Zhao

Sbert

et al. 2021

The Computer Journal

View full text Add to dashboard Cite

show abstract

“…It also provides a solution for the issue between HDR imaging and LDR display devices [6]. Various MEF algorithms have been proposed in recent years [7–21].…”

Section: Introductionmentioning

confidence: 99%