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Inverse tone mapping

Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia, 2006
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 dual of tone mapping, inverse tone mapping, expands a Low Dynamic Range Image (LDRI) into a HDRI.
Francesco Banterle, Patrick Ledda, Kurt Debattista, Alan Chalmers   +3 more
core   +4 more sources

Deep Inverse Tone Mapping for Compressed Images [PDF]

IEEE Access, 2019
Converting a single low dynamic range (LDR) image into a high dynamic range (HDR) image, which is the so-called inverse tone mapping (ITM), is a challenging ill-posed problem since a lot of information is lost during compression and storage.
Chao Wang, Yang Zhao, Ronggang Wang
doaj   +2 more sources

Semantic Aware Diffusion Inverse Tone Mapping [PDF]

Journal of Physics: Conference Series
Abstract Capturing the full luminance range of real-world scenes exceeds the capabilities of most digital cameras, often resulting in detail loss, particularly in bright regions. Inverse tone mapping aims to reconstruct High Dynamic Range (HDR) images from Standard Dynamic Range (SDR) inputs, but typically fails to recover clipped ...
Goswami A., Sing A. R., Banterle F., Debattista K., Bashford-Rogers T.   +4 more
core   +5 more sources

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping [PDF]

APSIPA Transactions on Signal and Information Processing, 2020
High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm.
Luzardo Morocho, Gonzalo Raimundo, Aelterman, Jan, Luong, Hiep, Rousseaux, Sven, Ochoa Donoso, Daniel, Philips, Wilfried   +5 more
openaire   +4 more sources

Forensic detection of inverse tone mapping in HDR images

2016 IEEE International Conference on Image Processing (ICIP), 2016
High dynamic range (HDR) imaging is attracting an increasing deal of attention in the multimedia community, yet its forensic problems have been little studied so far. This paper proposes an HDR image forensic method, which aims at differentiating HDR images created from multiple low dynamic range (LDR) images from those created from a single LDR image ...
Wei Fan 0004, Giuseppe Valenzise, Francesco Banterle, Frédéric Dufaux   +3 more
core   +7 more sources

Chinese and English Infants’ Tone Perception: Evidence for Perceptual Reorganization. [PDF]

, 2006
Over half the world’s population speaks a tone language, yet infant speech perception research has typically focused on consonants and vowels. Very young infants can discriminate a wide range of native and nonnative consonants and vowels, and then in a ...
Burnham, Denis, Mattock, Karen
core   +5 more sources

Multi-Exposure Fusion With Guidance Information: Night Color Image Enhancement for Roadside Units

IEEE Access, 2023
The computer vision-based roadside occupation surveillance system is a key infrastructure component of Cooperative Intelligent Transport Systems. However, traffic images captured under low-light conditions suffer from low visibility and unexpected noise.
Chen Yaqing, Wang Huaming
doaj   +1 more source

Derivatives and inverse of cascaded linear+nonlinear neural models. [PDF]

PLoS ONE, 2018
In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences. However, the conventional literature is usually too focused on only describing the forward input-output transform.
M Martinez-Garcia, P Cyriac, T Batard, M Bertalmío, J Malo   +4 more
doaj   +1 more source

Lightness Modulated Deep Inverse Tone Mapping

CoRR, 2021
11 pages, 10 ...
Kanglin Liu, Gaofeng Cao, Jiang Duan, Guoping Qiu   +3 more
openaire   +2 more sources

Dynamic Range Expansion Using Cumulative Histogram Learning for High Dynamic Range Image Generation

IEEE Access, 2020
In modern digital photographs, most images have low dynamic range (LDR) formats, which means that the range of light intensities from the darkest to the brightest is much lower than the range that can be perceived by the human eye.
Hanbyol Jang, Kihun Bang, Jinseong Jang, Dosik Hwang   +3 more
doaj   +1 more source