An enhancement algorithm based on multi-grayscale fusion and edge-weight for low contrast X-ray image

X-ray images of various complicated components have the issue of poor contrast, which prevents the structural information from being completely portrayed. A straightforward and efficient enhancement method based on multi-grayscale fusion and edge-weight is proposed to improve the quality of X-ray images. This approach makes use of several established image processing techniques. First, multiple derived images with various grayscales are obtained using three contrast adjustment techniques. The Laplacian pyramid, Gaussian-weighted pyramid, and principal component analysis (PCA) algorithm are then utilized to create a fusion image that displays overall structural information. The bilateral and guided filters are employed to generate an edgeweighted image that contains a lot of edge information. Finally, the edge-weighted image is performed by an exponential operation on the fusion image to obtain a high-contrast image, which is crucial to enhance the detailed features of the image. The experimental results demonstrate that the proposed method beats previous comparison algorithms in the quantitative index and is capable of fully presenting the internal structures of the samples. Additionally, the enhanced image is satisfactory in detail enhancement, local contrast improvement, and visual sensation.