Chest Radiographic Image Enhancement Based on Multi-Scale Retinex Technique

Author(s):  
Shuyue Chen ◽  
Ling Zou
2015 ◽  
Vol 9 (11) ◽  
pp. 943-950 ◽  
Author(s):  
Changying Dang ◽  
Yulin Xiao ◽  
Jianmin Gao ◽  
Zhao Wang ◽  
Fumin Chen

2019 ◽  
Vol 8 (4) ◽  
pp. 11228-11236

In this paper, automatic weld defect segmentation into the radiographic image non-destructive evaluation and testing, with orthogonal polynomials transformation-enhancement (OPT-E) is presented. This proposed system defect identification the given defect Radiographic image. In digital radiographic images, the unknown masses appear very light with weak edges, and hence image enhancement technique needs to be applied with transform domain and radiographic images of some illustrative weld deserts invent. The proposed scheme has three phases. In first phase, a radiographic image enhancement technique, which is performed by logarithmic common variance and enhancement factor, computed from the absolute value of the orthogonal polynomials transformation coefficient as principal parameters for increasing the energy of the masses in the digital radiographic image enhancement. In case of successful enhanced of image in addition to gradient estimation scheme is working to point the edges current, in the next phase. The consequential edge image is again applied with orthogonal polynomials. In the final phase, edge tracking are the salient features with angle based defect identification. Experimental is improved quality of images and high relative segmentation by OPT-E.


2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang

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.


Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Huajun Song ◽  
Rui Wang

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.


Sign in / Sign up

Export Citation Format

Share Document