scholarly journals Pseudo-Multiple-Exposure-based Tone Fusion and Visual-Salience-based Tone Mapping for High Dynamic Range Images: A Review

2015 ◽  
Vol 127 (8) ◽  
pp. 41-46
Author(s):  
Sadaf Afreen ◽  
Aizaz Tirmizi ◽  
Mohd. Sarwar
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Images ◽  
Visual Salience ◽  
Multiple Exposure ◽  
High Dynamic

scholarly journals Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection

2019 ◽  
Vol 9 (21) ◽  
pp. 4658
Author(s):  
Ho-Hyoung Choi ◽  
Hyun-Soo Kang ◽  
Byoung-Ju Yun
Keyword(s):  
Computer Vision ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Base Layer ◽  
Tone Mapping ◽  
Range Images ◽  
Visual Salience ◽  
Image Size ◽  
High Dynamic ◽  
Weighting Methods

One of the significant qualities of the human vision, which differentiates it from computer vision, is so called attentional control, which is the innate ability of our human eyes to select what visual stimuli to pay attention to at any moment in time. In this sense, the visual salience detection model, which is designed to simulate how the human visual system (HVS) perceives objects and scenes, is widely used for performing multiple vision tasks. This model is also in high demand in the tone mapping technology of high dynamic range images (HDRIs). Another distinct quality of the HVS is that our eyes blink and adjust brightness when objects are in their sight. Likewise, HDR imaging is a technology applied to a camera that takes pictures of an object several times by repeatedly opening and closing a camera iris, which is referred to as multiple exposures. In this way, the computer vision is able to control brightness and depict a range of light intensities. HDRIs are the product of HDR imaging. This article proposes a novel tone mapping method using CCH-based saliency-aware weighting and edge-aware weighting methods to efficiently detect image salience information in the given HDRIs. The two weighting methods combine with a guided filter to generate a modified guided image filter (MGIF). The function of the MGIF is to split an image into the base layer and the detail layer which are the two elements of an image: illumination and reflection, respectively. The base layer is used to obtain global tone mapping and compress the dynamic range of HDRI while preserving the sharp edges of an object in the HDRI. This has a remarkable effect of reducing halos in the resulting HDRIs. The proposed approach in this article also has several distinct advantages of discriminative operation, tolerance to image size variation, and minimized parameter tuning. According to the experimental results, the proposed method has made progress compared to its existing counterparts when it comes to subjective and quantitative qualities, and color reproduction.

High Dynamic Range Images and Tone Mapping Operator

2009 ◽  
Vol 35 (2) ◽  
pp. 113-122 ◽  
Author(s):  
Ke-Hu YANG ◽  
Jing JI ◽  
Jian-Jun GUO ◽  
Wen-Sheng YU
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Images ◽  
High Dynamic

scholarly journals Deep Tone Mapping Operator for High Dynamic Range Images

2020 ◽  
Vol 29 ◽  
pp. 1285-1298 ◽  
Author(s):  
Aakanksha Rana ◽  
Praveer Singh ◽  
Giuseppe Valenzise ◽  
Frederic Dufaux ◽  
Nikos Komodakis ◽  
...  
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Images ◽  
High Dynamic
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