Research on Endoscopic Image Enhancement Algorithm Based on Contrast Fusion

Image enhancement can improve doctors' perception of gastrointestinal tissues and blood vessels. This paper introduces an image enhancement method for medical endoscopy, which includes three stages: (1) improved contrast enhancement algorithm, using multiple iterative sharpening mask to enhance the edge contour of gastrointestinal tissues and blood vessels; (2) improved limiting threshold of limiting contrast adaptive histogram equalization (CLAHE); (3) improved contrast image fusion to preserve the good characteristics of improved contrast enhancement algorithm and improved CLAHE. The proposed method is applied to large data sets of low contrast white light endoscopes. The experimental results show that the endoscopic image enhancement algorithm based on contrast fusion is a feasible method to solve the defects between different image enhancement algorithms, because the image fusion results can effectively reduce the defects of contrast enhancement algorithm and CLAHE compared with the original image, such as detail loss, local contrast loss and pixel value loss.