Adaptive Noise Reduction Algorithm for an Image Based on a Bayesian Method
- Authors
- 김영화; 남지호
- Issue Date
- Jul-2012
- Publisher
- 한국통계학회
- Keywords
- Bartlett's test; Bayesian statistics; image processing; MAP; noise; noise reduction.
- Citation
- Communications for Statistical Applications and Methods, v.19, no.4, pp 619 - 628
- Pages
- 10
- Journal Title
- Communications for Statistical Applications and Methods
- Volume
- 19
- Number
- 4
- Start Page
- 619
- End Page
- 628
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/35514
- DOI
- 10.5351/CKSS.2012.19.4.619
- ISSN
- 2287-7843
- Abstract
- Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise;however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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