로버스트 회귀모형에 근거한 영상 잡음 제거 필터

Image Noise Reduction Filter Based on Robust Regression Model
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초록

Digital images acquired by digital devices are used in many fields. Applying statistical methods to the processing of images will increase speed and efficiency. Methods to remove noise and image quality have been researched as a basic operation of image processing. This paper proposes a novel reduction method that considers the direction and magnitude of the edge to remove image noise effectively using statistical methods. The proposed method estimates the brightness of pixels relative to pixels in the same direction based on a robust regression model. An estimate of pixel brightness is obtained by weighting the magnitude of the edge that improves the performance of the average filter. As a result of the simulation study, the proposed method retains pixels that are well-characterized and confirms that noise reduction performance is improved over conventional methods.

키워드

Bartlett test; image processing; noise reduction; robust regression model
제목
로버스트 회귀모형에 근거한 영상 잡음 제거 필터
제목 (타언어)
Image Noise Reduction Filter Based on Robust Regression Model
저자
김영화; 박영호
DOI
10.5351/KJAS.2015.28.5.991
발행일
2015-10
유형
Article
저널명
응용통계연구
권
28
호
5
페이지
991 ~ 1001