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

Atsushi Teramoto, Isao Horiba, Noboru Sugie

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages190-194
Number of pages5
Publication statusPublished - 1997
Externally publishedYes
EventProceedings of the 1997 1st International Conference on Information, Communications and Signal Processing, ICICS. Part 3 (of 3) - Singapore, Singapore
Duration: 09-09-199712-09-1997

Conference

ConferenceProceedings of the 1997 1st International Conference on Information, Communications and Signal Processing, ICICS. Part 3 (of 3)
CitySingapore, Singapore
Period09-09-9712-09-97

All Science Journal Classification (ASJC) codes

  • Signal Processing

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