Image feature and noise detection based on statistical hypothesis tests and their applications in noise reduction
- Authors
- Kim, Yeong-Hwa; Lee, Jae Heon
- Issue Date
- Nov-2005
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- chi-squared distribution; image processing; order statistics; feature and noise detection; statistical hypothesis test
- Citation
- IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, v.51, no.4, pp 1367 - 1378
- Pages
- 12
- Journal Title
- IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
- Volume
- 51
- Number
- 4
- Start Page
- 1367
- End Page
- 1378
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/24491
- DOI
- 10.1109/TCE.2005.1561869
- ISSN
- 0098-3063
1558-4127
- Abstract
- In many video processing applications in the field of consumer electronics such as Digital TV, it is well understood that the presence of a noise limits the performance of video enhancement functions due to the. time-varying characteristics of the noise. The basic difficulty is that the noise and the signal are difficult to be distinguished. This paper proposes image feature and noise detection algorithms which effectively distinguish the noise from the image feature or vice versa. Specifically, the proposed algorithms provide a way of measuring the degree of noise with respect to the degree of image feature. The,fundamental idea behind the proposed algorithms is to derive a statistical measure to estimate the fact that a noise has a random characteristic whereas an image feature has a spatial correlation among the associated neighbor samples. With the proposed algorithms, many video enhancement algorithms such as noise reduction or sharpness enhancement can be adaptively performed although a time varying noise is presented.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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