Medical Image Enhancement Algorithm Based on Biorthogonal Wavelet.

Medical imaging technology has become an important tool to conduct non-invasive detection on human body in medical diagnosis. Therefore, image quality is particularly significant. As wavelet transform has excellent local time-frequency properties as well as features of multi-scale and multi-resolution, it holds an enormous advantage in digital image processing. After wavelet transform, edge detail information of the image is distributed in different decomposition scales and for different decomposition scales, edge information has different features. All traditional image enhancement algorithms based on wavelet obtain detail information by decomposing low-frequency sub-image and there is still plenty of detail information in high-frequency subimages. On this basis, this paper makes improvements to the traditional image decomposition methods; raises the method to get more detail information by further high-frequency sub-image and a new image enhancement algorithm for edge detection based on bi-orthogonal wavelet; and uses this algorithm in medical image enhancement. In another word, it firstly performs n-level wavelet decomposition on the image and gets the approximate low-frequency information and high-frequency information of the image. Then, it adopts different methods to handle the wavelet coefficients obtained, namely it processes the high-frequency wavelet coefficients or all wavelet coefficients with different enhancement algorithms. Finally, it reconstructs the wavelet coefficients processed to obtain the enhanced medical image. [ABSTRACT FROM AUTHOR]