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Entropy 2018, 20(12), 935; https://doi.org/10.3390/e20120935

A Novel Multi-Exposure Image Fusion Method Based on Adaptive Patch Structure

1
School of Information and Electrical, China University of Mining and Technology, Xuzhou 221116, China
2
College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3
College of Automation, Chongqing University, Chongqing 400044, China
4
Department of Mathematics and Computer Information Science, Mansfield University of Pennsylvania, Mansfield, PA 16933, USA
5
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
*
Author to whom correspondence should be addressed.
Received: 29 October 2018 / Revised: 3 December 2018 / Accepted: 3 December 2018 / Published: 6 December 2018
(This article belongs to the Special Issue Entropy in Image Analysis)
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Abstract

Multi-exposure image fusion methods are often applied to the fusion of low-dynamic images that are taken from the same scene at different exposure levels. The fused images not only contain more color and detailed information, but also demonstrate the same real visual effects as the observation by the human eye. This paper proposes a novel multi-exposure image fusion (MEF) method based on adaptive patch structure. The proposed algorithm combines image cartoon-texture decomposition, image patch structure decomposition, and the structural similarity index to improve the local contrast of the image. Moreover, the proposed method can capture more detailed information of source images and produce more vivid high-dynamic-range (HDR) images. Specifically, image texture entropy values are used to evaluate image local information for adaptive selection of image patch size. The intermediate fused image is obtained by the proposed structure patch decomposition algorithm. Finally, the intermediate fused image is optimized by using the structural similarity index to obtain the final fused HDR image. The results of comparative experiments show that the proposed method can obtain high-quality HDR images with better visual effects and more detailed information. View Full-Text
Keywords: multi-exposure image fusion; texture information entropy; adaptive selection; patch structure decomposition multi-exposure image fusion; texture information entropy; adaptive selection; patch structure decomposition
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Li, Y.; Sun, Y.; Zheng, M.; Huang, X.; Qi, G.; Hu, H.; Zhu, Z. A Novel Multi-Exposure Image Fusion Method Based on Adaptive Patch Structure. Entropy 2018, 20, 935.

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