A novel medical image enhancement algorithm based on improvement correction strategy in wavelet transform domain

Since medical image is often corrupted by all kinds of noises during acquisition or transmission, this will lead to the degradation of the image quality, which further seriously affects the clinical diagnoses. In order to solve the degradation problem and enhance image quality, a novel medical image enhancement algorithm based on improvement correction strategy in wavelet transform domain is proposed in paper. Firstly, the image is decomposed into high-frequency component and low-frequency component by Shear wavelet transform. Secondly, the low-frequency component in wavelet domain is processed by the improved correction method so as to adjust the global contrast of the image, and the improved adaptive threshold function is adopted to reduce the high-frequency noise. Finally, the reconstructed image from inverse wavelets transform is proposed by fuzzy contrast enhancement to highlight the image detail while maintaining excellent spectral information. Many simulation experiments show that our proposed algorithm achieves more favorable performance for the non-reference evaluation and the reference evaluation than these existing state-of-the-art algorithms in handing medicine images, which can effectively improve the image quality. This performance increase is the most pronounced in indexes for our proposed enhancement algorithm, which can raise the rate of conformity in clinical diagnoses.