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A framework for inverse tone mapping

Visual Computer, 2007
In recent years many tone mapping operators (TMOs) have been presented in order to display high dynamic range images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The inverse of tone mapping, inverse tone mapping, expands a low dynamic range image (LDRI) into an HDRI.
Francesco Banterle   +2 more
exaly   +2 more sources

Content-adaptive inverse tone mapping

2012 Visual Communications and Image Processing, 2012
Tone mapping is an important technique used for displaying high dynamic range (HDR) content on low dynamic range (LDR) devices. On the other hand, inverse tone mapping enables LDR content to appear with an HDR effect on HDR displays. The existing inverse tone mapping algorithms usually focus on enhancing the luminance in over-exposed regions with less (
Shao-Yi Chien
exaly   +2 more sources

Deep Video Inverse Tone Mapping

2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM), 2019
Inverse tone mapping is an important topic in High Dynamic Range technology. Recent years, deep learning based image inverse tone mapping methods have been extensively studied and perform better than classical inverse tone mapping methods. However, these methods consider the inverse tone mapping problem as a domain transformation problem from LDR ...
Li Song, Rong Xie, Wenjun Zhang
exaly   +2 more sources

Physiological inverse tone mapping based on retina response

Visual Computer, 2013
The mismatch between the Low Dynamic Range (LDR) content and the High Dynamic Range (HDR) display arouses the research on inverse tone mapping algorithms. In this paper, we present a physiological inverse tone mapping algorithm inspired by the property of the Human Visual System (HVS).
YongQing Huo, Le Dong
exaly   +2 more sources

A brightness-adaptive kernel prediction network for inverse tone mapping

Neurocomputing, 2021
Abstract The inverse tone mapping (iTM) technique that produces a high dynamic range (HDR) image from one single standard dynamic range (SDR) image has received much attention in industry and academia recently. However, existing methods to recover HDR images mainly focus on overexposed regions but ignore underexposed regions. The underexposed regions
Gaofeng Cao, Fei Zhou, Kanglin Liu
exaly   +2 more sources

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