Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
531950 | Pattern Recognition | 2006 | 6 Pages |
Abstract
Techniques of noise detection have been widely applied in impulse noise reduction. However, the phenomenon of pixel misclassification is very obvious in high noise density. In order to improve pixel identification, in this paper, the new noise detector is proposed. Based on solutions of equations, an estimated block of every 8×88×8 block of a noise image is generated. Then, according to relationships between these noise blocks and their estimated blocks, corrupted and uncorrupted pixels are identified. During image filtering, a noise-detection-based adaptive median algorithm is presented. Experimental results show that the proposed filter can well reduce the impulse noise and preserve more details of original images.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Shi-Qiang Yuan, Yong-Hong Tan,