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- Title
基于Retinex模型和GTV的铁路 货车铸件DR图像增强.
- Authors
任雨霞; 曾理
- Abstract
Railway transportation has become one of the most important transportation modes in China. Casting defects (pores, cracks, etc.) of railway freight car parts (such as pillow or side frame) may cause traffic accidents. Since the inhomogeneity of the railway castings could cause uneven gray scale of the original DR images, it is difficult to capture the defect details. Therefore, image enhancement and other operations should be performed on the original DR images to detect the defects. The model based on Retinex takes into account both the illumination intensity and material information of the target and decomposes the images into illumination and reflection ones. The protective image edge filter based on Gaussian Total Variation (GTV) can smooth the illumination images and remove the texture details of the illumination images so that the details of defects are exposed in the reflection image. For defect identification of railway truck castings, an improved Retinex enhanced model was proposed, which used GTV and texture perception based weights to regularize the illumination and reflection maps in the process of Retinex decomposition. In addition, an alternative optimization algorithm was used to solve the model. Finally, the reflection image reflecting the details of the image defect was used as the final enhanced image. The image obtained by this method not only retains the structure information of the image, but also obviously exposes the defect details of the image. The experimental results show that compared with other existing models, this model enhances the defects significantly. In addition, the information entropy and mean gradient of DR Images were improved. Compared with the original images, the information entropy of the enhanced image was increased by more than 8%, and the average gradient was increased by at least 6 times. This method improved the ability of DR image detection and can be applied to non-destructive testing of railway truck castings.
- Subjects
CHINA; OPTIMIZATION algorithms; NONDESTRUCTIVE testing; IMAGE intensifiers; FREIGHT cars; TRAFFIC accidents
- Publication
Journal of Railway Science & Engineering, 2023, Vol 20, Issue 2, p706
- ISSN
1672-7029
- Publication type
Article
- DOI
10.19713/j.cnki.43-1423/u.T20220356