Improvement of image quality in MR image using adaptive K-nearest neighbor averaging filter

In this paper, a new filter for the purpose of restoring MR image from noise-contaminated ones is proposed. The filter is an extension of non-linear filter, known as K-nearest neighbor averaging Filter (KF). In the KF, filter parameter k is constant over the whole image. In the proposed method, the filter parameter k is changed on the basis of some characteristic values in the local region. As characteristic values, pixel value and gradient of pixel value are employed. Furthermore, characteristic value which detects the salt-and-pepper noise in MR is also employed. In the experiments, the proposed method as well as the conventional one is applied to MR images. As a result, noise smoothing avoiding degradation of edge has been carried out. Furthermore, we evaluate the frequency response using modulation transfer function. Its results have indicated the mechanism of noise reduction in AKF.