The application of adaptive enhancement algorithm based on gray entropy in mammary gland CR image

Mammary gland is composed entirely of soft tissue with approximate density, therefore mammary gland CR medicine radiation image presents a low contrast, and slight difference changes may be a manifestation of tumor, so it is necessary to enhance mammary gland CR image to improve its visual quality in order to meet the demands of doctor´s clinical diagnosis. However the general enhancement algorithms over enhance the contrast and noise, due to image details lost, aiming at the defects, a mammary gland CR medicine image adaptive enhancement arithmetic based on image gray entropy is put forward. The arithmetic adapts dizzy image to magnify selected spatial frequency response in order to enhance the edge details of mammary gland CR images. It can adjust weighted factor K according to image gray characteristics namely pixel gray entropy. Experiments results demonstrate that mammary gland CR image enhanced by the algorithm has abundant details and high signal-to-noise ratio, moreover, CR image enhanced has good visual effect. So the method is effective and fit for enhancing CR medical radiation image edge details.