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67‐2: Lightweight Tone‐mapped HDRNET with Exposure Stack Generation
Author(s) -
Jo So Yeon,
Ahn Namhyun,
Kang Suk-Ju
Publication year - 2020
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/sdtp.14040
Subject(s) - tone mapping , tone (literature) , stack (abstract data type) , computer science , high dynamic range , artificial intelligence , image (mathematics) , computer vision , range (aeronautics) , artificial neural network , dynamic range , computer graphics (images) , engineering , art , literature , programming language , aerospace engineering
In this paper, we propose an efficient and lightweight deep neural network, LW‐HDRNET, which quickly and accurately reconstructs tone‐mapped high dynamic range (HDR) images. The proposed network generates over‐exposed and under‐exposed images from a single LDR image and then reconstructs the tone‐mapped HDR image. Experimental results show that the performance is better than the existing methods and has up to 4,000 times fewer parameters.