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Tytuł:
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A New Photographic Reproduction Method Based on Feature Fusion and Virtual Combined Histogram Equalization.
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Autorzy:
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Lin YH; Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, Taiwan.
Hua KL; Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Chen YY; Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Chen IY; Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, Taiwan.
Tsai YC; Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106, Taiwan.
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Źródło:
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Sensors (Basel, Switzerland) [Sensors (Basel)] 2021 Sep 09; Vol. 21 (18). Date of Electronic Publication: 2021 Sep 09.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: Basel, Switzerland : MDPI, c2000-
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MeSH Terms:
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Data Compression*
Image Enhancement*
Algorithms ; Photography ; Reproduction
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References:
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IEEE Trans Image Process. 2013 Feb;22(2):657-67. (PMID: 23047872)
IEEE Trans Image Process. 2017 Dec;26(12):5936-5949. (PMID: 28816664)
IEEE Trans Image Process. 2012 Dec;21(12):4695-708. (PMID: 22910118)
IEEE Trans Image Process. 2013 Jan;22(1):70-9. (PMID: 22910115)
IEEE Trans Vis Comput Graph. 2005 Jan-Feb;11(1):13-24. (PMID: 15631125)
IEEE Trans Image Process. 2015 Aug;24(8):2579-91. (PMID: 25915960)
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Grant Information:
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MOST 108-2221-E-027 -095 -MY2 Ministry of Science and Technology
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Contributed Indexing:
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Keywords: feature fusion; histogram equalization; human visual system; photographic reproduction; virtual combined histogram; vision sensing technique
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Entry Date(s):
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Date Created: 20210928 Date Completed: 20210929 Latest Revision: 20211001
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Update Code:
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20240105
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PubMed Central ID:
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PMC8471737
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DOI:
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10.3390/s21186038
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PMID:
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34577244
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A desirable photographic reproduction method should have the ability to compress high-dynamic-range images to low-dynamic-range displays that faithfully preserve all visual information. However, during the compression process, most reproduction methods face challenges in striking a balance between maintaining global contrast and retaining majority of local details in a real-world scene. To address this problem, this study proposes a new photographic reproduction method that can smoothly take global and local features into account. First, a highlight/shadow region detection scheme is used to obtain prior information to generate a weight map. Second, a mutually hybrid histogram analysis is performed to extract global/local features in parallel. Third, we propose a feature fusion scheme to construct the virtual combined histogram, which is achieved by adaptively fusing global/local features through the use of Gaussian mixtures according to the weight map. Finally, the virtual combined histogram is used to formulate the pixel-wise mapping function. As both global and local features are simultaneously considered, the output image has a natural and visually pleasing appearance. The experimental results demonstrated the effectiveness of the proposed method and the superiority over other seven state-of-the-art methods.
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