Multi-step radiographic image enhancement conforming to weld defect segmentation


To improve the accuracy of automatic defect segmentation in radiographic non-destructive testing and analysis, the authors proposed a multi-step radiographic image enhancement algorithm (MSRE) conforming to weld defect segmentation. In this algorithm, the necessity of defect segmentation is absolutely thought of when enhancing a radiographic testing image. The primary-step enhancement is performed by linear weighting between an ingenious radiographic image and its contrast-limited adaptive histogram equalisation image. Anisotropic diffusion filtering is used for simultaneously smoothing the weighted image and preserving the defect edges terribly well. Then, the filtered image is enhanced by a fuzzy enhancement algorithm as the final-step enhancement and hence, getting a brand new image with high contrast, high definition, and sturdy edge intensity. The authors compared MSRE with adaptive histogram equalisation, fuzzy enhancement, world distinction enhancement, and local contrast enhancement algorithms and evaluated its performance by using indicators like image contrast, definition, edge intensity, and information entropy. Furthermore, the authors compared the segmentation results of the improved images to more study the algorithm's effect on weld defect segmentation. Experimental results reveal that the standard of enhanced pictures is significantly improved by MSRE, and the image enhanced by MSRE has an high relative segmentation accuracy (RSA) of a lot of than 95percent.

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