[Medical image processing based on wavelet characteristics and edge blur detection].

ABSTRACT

To solve the problems of noise interference and edge signal weakness for the existing medical image, we used two-dimensional wavelet transform to process medical images. Combined the directivity of the image edges and the correlation of the wavelet coefficients, we proposed a medical image processing algorithm based on wavelet characteristics and edge blur detection. This algorithm improved noise reduction capabilities and the edge effect due to wavelet transformation and edge blur detection. The experimental results showed that directional correlation improved edge based on wavelet transform fuzzy algorithm could effectively reduce the noise signal in the medical image and save the image edge signal. It has the advantage of the high-definition and de-noising ability.