A novel medical image enhancement method based on wavelet multi-resolution analysis

Aimed to resolve the problem of visual effect to the medical image in clinic practice and offer more important diagnostic information for surgery, the paper using wavelet multi-level analysis theory designed a novel medical image enhancement algorithm. Firstly, the traditional wavelet transform is performed to original medical images; consequently, the wavelet transform coefficients are extracted using wavelet transformation. Secondly, coefficients are divided into two groups according to the contribution to the original medical image. The soft threshold is introduced and reprocessed to reconstruct the image information. At last, the inverse of wavelet transform (IWT) is made in order to generate the result image. The wavelet transform can render the details of feature with the scale of different separation, so the different resolutions of detail feature in the original image are enhanced. Compared with the original medical images, the results images have better results of vision effect, it can offered more accurate and detailed information to doctor, so it can be used in medical diagnose in our life. Many valuable experiments are made to validate the feasibility and efficiency.