Adaptive filtering for medical image based on tensor field

Tensor fields specifically, matrix valued data sets, have recently attracted increased attention in the fields of image processing, computer vision, visualization and medical imaging. In this paper, we present a novel image denoising algorithm based on tensor field analysis in concepts from non-iterative. According the characteristic of tensor filed can externalize the local orientation information which can control the size, shape and orientation of the filter. We have compared our algorithm with Wiener algorithm. Our algorithm contains more configuration information better than Wiener algorithm. The results are very good on a wide variety of images from moderate SNR to low SNR. The algorithm is tested on real medical image data (CT, X-Ray)and improved for this special application.