Image Feature Detection and Contrast Enhancement Algorithms Based on Statistical Tests
- Authors
- 김영화; 남지호
- Issue Date
- Jun-2007
- Publisher
- 한국데이터정보과학회
- Keywords
- Image Enhancement; Image Processing; Image Enhancement; Image Processing
- Citation
- 한국데이터정보과학회지, v.18, no.2, pp 385 - 399
- Pages
- 15
- Journal Title
- 한국데이터정보과학회지
- Volume
- 18
- Number
- 2
- Start Page
- 385
- End Page
- 399
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/30055
- ISSN
- 1598-9402
- Abstract
- In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.
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