An improved algorithm of multi-exposure image fusion by detail enhancement
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An improved algorithm of multi‑exposure image fusion by detail enhancement Zhong Qu1 · Xu Huang1 · Ling Liu1 Received: 15 January 2020 / Accepted: 5 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Multi-exposure image fusion is an effective method for depicting high dynamic range of the target scene in a single image. However, there are still some problems remaining: the preserving of global contrast, the preserving of the local details in saturated regions, and the existence of halo artifacts. To solve these problems, this paper proposes a new multi-exposure image fusion algorithm with detail enhancement. Firstly, the well-exposedness evaluation function, the chromatic information evaluation function and the local detail preserved function are used to measure weight maps. Then, an improved multi-exposure fusion framework based on pyramid decomposition is proposed to further enhance the details. The experimental results demonstrate that the proposed algorithm can preserve more details than the state-of-the-art. In the view of appreciation, our approach could produce a more realistic brightness distribution of target scene as well as avoid halo artifacts. Keywords Weight measurement function · Details enhancement · Image fusion · HDR
1 Introduction WITH the development of computer vision, consumers are demanding greater and more vivid visual experiences. Due to the limitation of the image sensor, the dynamic range of an ordinary digital camera is far lower than the natural scene, the captured images often show regions that are “too bright” or “too dark” [1–3]. High dynamic range (HDR) imaging technology is designed to solve this problem [4–7]. In general, the existing HDRI methods can be divided into two categories: the tone mapping based method and the multiexposure image fusion based method [8–10]. Tone mapping based methods require HDR image data acquisition in advance, and show HDR images on the low dynamic range (LDR) displays using tone mapping techniques [11–14]. The method based on multi-exposure fusion skips the step of acquiring HDR image data and yields a tone mappedlike fused image directly, therefore, it generally takes less time to depict a high dynamic range of images than the tone Communicated by X. Yang. * Zhong Qu [email protected] 1
Chongqing University of Posts and Telecommunications, Chongqing, China
mapping method [15–17]. In this paper, we achieve HDRI based on multi-exposure image fusion algorithm by merging multiple image sequences with different exposures. The primary goal of the multi-exposure fusion algorithm is to show a high dynamic range (HDR) target scene in a LDR image [18]. In recent years, many researchers have investigated multi-exposure fusion algorithms. Mertens et al. [19] proposed a multi-exposure image fusion algorithm based on the pyramid decomposition, i.e., Laplacian pyramids of LDR images and Gaussian pyramids of weight maps consist of contrast, saturation and well-exposedness, but at the cost of local infor
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