Multi-scale retinex color restoration with adaptive gamma correction for foggy image enhancement

Author(s):  
Bin Wei ◽  
Lu Li
2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He

The retinex is a human perception based image processing algorithm which provides color constancy and dynamic range compression. The multi scale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. But the MSRCR results suffer from lower global brightness and partial color distortion. In order to improve the MSRCR method, this paper presents a modified MSRCR algorithm to Landsat-5 image enhancement considering percent liner stretch and histogram adjustment. Finally, the effect of modified MSRCR method on Landsat-5 image enhancement is analyzed and the comparison with other color adjustment methods such as gamma correction and histogram equalization is reported in the experimental results.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 24
Author(s):  
Yan-Tsung Peng ◽  
He-Hao Liao ◽  
Ching-Fu Chen

In contrast to conventional digital images, high-dynamic-range (HDR) images have a broader range of intensity between the darkest and brightest regions to capture more details in a scene. Such images are produced by fusing images with different exposure values (EVs) for the same scene. Most existing multi-scale exposure fusion (MEF) algorithms assume that the input images are multi-exposed with small EV intervals. However, thanks to emerging spatially multiplexed exposure technology that can capture an image pair of short and long exposure simultaneously, it is essential to deal with two-exposure image fusion. To bring out more well-exposed contents, we generate a more helpful intermediate virtual image for fusion using the proposed Optimized Adaptive Gamma Correction (OAGC) to have better contrast, saturation, and well-exposedness. Fusing the input images with the enhanced virtual image works well even though both inputs are underexposed or overexposed, which other state-of-the-art fusion methods could not handle. The experimental results show that our method performs favorably against other state-of-the-art image fusion methods in generating high-quality fusion results.


2020 ◽  
Author(s):  
Jingyu Yang ◽  
Yuwei Xu ◽  
Huanjing Yue ◽  
Zhongyu Jiang ◽  
Kun Li

Author(s):  
Shanto Rahman ◽  
Md Mostafijur Rahman ◽  
M. Abdullah-Al-Wadud ◽  
Golam Dastegir Al-Quaderi ◽  
Mohammad Shoyaib

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