Improved multi-scale Retinex infrared image enhancement

2021 ◽  
Vol 36 (3) ◽  
pp. 465-474
Author(s):  
Ran-ran WEI ◽  
◽  
Wei-da ZHAN ◽  
De-peng ZHU ◽  
Yong TIAN
Keyword(s):  
Image Enhancement ◽  
Infrared Image ◽  
Multi Scale

scholarly journals An Adaptive Detail Equalization for Infrared Image Enhancement Based on Multi-Scale Convolution

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 156763-156773
Author(s):  
Haoxiang Lu ◽  
Zhenbing Liu ◽  
Xipeng Pan
Keyword(s):  
Image Enhancement ◽  
Infrared Image ◽  
Multi Scale

An improved infrared image enhancement algorithm based on multi-scale decomposition

2014 ◽  
Author(s):  
Honghui Zhang ◽  
Haibo Luo ◽  
Xin-rong Yu ◽  
Qing-hai Ding
Keyword(s):  
Image Enhancement ◽  
Infrared Image ◽  
Multi Scale ◽  
Enhancement Algorithm

Infrared image enhancement through saliency feature analysis based on multi-scale decomposition

2014 ◽  
Vol 62 ◽  
pp. 86-93 ◽  
Author(s):  
Jufeng Zhao ◽  
Yueting Chen ◽  
Huajun Feng ◽  
Zhihai Xu ◽  
Qi Li
Keyword(s):  
Image Enhancement ◽  
Infrared Image ◽  
Feature Analysis ◽  
Multi Scale

Multi scale detail-preserving denoising method of infrared image via relative total variation

2013 ◽  
Author(s):  
Guang-mang Cui ◽  
Hua-jun Feng ◽  
Zhi-hai Xu ◽  
Qi Li ◽  
Yue-ting Chen
Keyword(s):  
Total Variation ◽  
Infrared Image ◽  
Denoising Method ◽  
Multi Scale ◽  
Relative Total Variation

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

scholarly journals Underwater Image Enhancement Based on Multi-Scale Fusion and Global Stretching of Dual-Model

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Huajun Song ◽  
Rui Wang
Keyword(s):  
Image Enhancement ◽  
Poor Performance ◽  
Weight Coefficient ◽  
Color Contrast ◽  
Dual Model ◽  
Spatial Cues ◽  
Multi Scale ◽  
Imaging Model ◽  
Underwater Image ◽  
Enhancement Method

Aimed at the two problems of color deviation and poor visibility of the underwater image, this paper proposes an underwater image enhancement method based on the multi-scale fusion and global stretching of dual-model (MFGS), which does not rely on the underwater optical imaging model. The proposed method consists of three stages: Compared with other color correction algorithms, white-balancing can effectively eliminate the undesirable color deviation caused by medium attenuation, so it is selected to correct the color deviation in the first stage. Then, aimed at the problem of the poor performance of the saliency weight map in the traditional fusion processing, this paper proposed an updated strategy of saliency weight coefficient combining contrast and spatial cues to achieve high-quality fusion. Finally, by analyzing the characteristics of the results of the above steps, it is found that the brightness and clarity need to be further improved. The global stretching of the full channel in the red, green, blue (RGB) model is applied to enhance the color contrast, and the selective stretching of the L channel in the Commission International Eclairage-Lab (CIE-Lab) model is implemented to achieve a better de-hazing effect. Quantitative and qualitative assessments on the underwater image enhancement benchmark dataset (UIEBD) show that the enhanced images of the proposed approach achieve significant and sufficient improvements in color and visibility.

A Modified Multi Scale Retinex with Color Restoration Algorithm for Automatic Enhancement of Landsat-5 Remote Sensing Image

2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Color Constancy ◽  
Human Perception ◽  
Histogram Equalization ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Dynamic Range Compression ◽  
Restoration Algorithm ◽  
Color Restoration

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.

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