Correcting Low Illumination Images Using PSO-Based Gamma Correction and Image Classifying Method

2021 ◽  
pp. 433-444
Author(s):  
Swadhin Das ◽  
Manali Roy ◽  
Susanta Mukhopadhyay
Keyword(s):  
Gamma Correction ◽  
Low Illumination

scholarly journals GLAGC: Adaptive Dual-Gamma Function for Image Illumination Perception and Correction in the Wavelet Domain

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 845
Author(s):  
Wenyong Yu ◽  
Haiming Yao ◽  
Dan Li ◽  
Gangyan Li ◽  
Hui Shi
Keyword(s):  
Discrete Wavelet ◽  
Exposure Level ◽  
Gamma Correction ◽  
Adaptive Stabilization ◽  
Low Contrast ◽  
Adaptive Correction ◽  
Low Illumination ◽  
Adaptive Gamma Correction ◽  
Entropy Criterion ◽  
The Relationship

Low-contrast or uneven illumination in real-world images will cause a loss of details and increase the difficulty of pattern recognition. An automatic image illumination perception and adaptive correction algorithm, termed as GLAGC, is proposed in this paper. Based on Retinex theory, the illumination of an image is extracted through the discrete wavelet transform. Two features that characterize the image illuminance are creatively designed. The first feature is the spatial luminance distribution feature, which is applied to the adaptive gamma correction of local uneven lighting. The other feature is the global statistical luminance feature. Through a training set containing images with various illuminance conditions, the relationship between the image exposure level and the feature is estimated under the maximum entropy criterion. It is used to perform adaptive gamma correction on global low illumination. Moreover, smoothness preservation is performed in the high-frequency subband to preserve edge smoothness. To eliminate low-illumination noise after wavelet reconstruction, the adaptive stabilization factor is derived. Experimental results demonstrate the effectiveness of the proposed algorithm. By comparison, the proposed method yields comparable or better results than the state-of-art methods in terms of efficiency and quality.

An adaptive enhancement algorithm based on visual saliency for low illumination images

2021 ◽  
Author(s):  
Shenyi Qian ◽  
Yongsheng Shi ◽  
Huaiguang Wu ◽  
Jinhua Liu ◽  
Weiwei Zhang
Keyword(s):  
Visual Saliency ◽  
Adaptive Enhancement ◽  
Low Illumination ◽  
Enhancement Algorithm

Automatic Gamma Correction Based on Root-Mean-Square-Error Maximization

2020 ◽  
Author(s):  
Ahmad S. Tarawneh ◽  
Ahmad B. Hassanat ◽  
Issam Elkhadiri ◽  
Dmitry Chetverikov ◽  
Khalid Almohammadi
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Mean Square ◽  
Gamma Correction

Low-illumination Image Enhancement for Night-time UAV Pedestrian Detection

2020 ◽  
pp. 1-1
Author(s):  
Weijiang Wang ◽  
Yeping Peng ◽  
Guangzhong Cao ◽  
Xiaoqin Guo ◽  
Ngaiming Kwok
Keyword(s):  
Image Enhancement ◽  
Pedestrian Detection ◽  
Night Time ◽  
Low Illumination

DEN: Disentanglement and Enhancement Networks for Low Illumination Images

2020 ◽  
Author(s):  
Nelson Chong Ngee Bow ◽  
Vu-Hoang Tran ◽  
Punchok Kerdsiri ◽  
Yuen Peng Loh ◽  
Ching-Chun Huang
Keyword(s):  
Low Illumination

Global brightness and local contrast adaptive enhancement for low illumination color image

Optik ◽  
2014 ◽  
Vol 125 (6) ◽  
pp. 1795-1799 ◽  
Author(s):  
Zhigang Zhou ◽  
Nong Sang ◽  
Xinrong Hu
Keyword(s):  
Color Image ◽  
Local Contrast ◽  
Adaptive Enhancement ◽  
Low Illumination
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