101. A two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter
- Author
-
Yufeng Nie and Hongjin Ma
- Subjects
Computer and Information Sciences ,Imaging Techniques ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Equipment ,Color ,lcsh:Medicine ,Transportation ,Image Analysis ,02 engineering and technology ,Digital Imaging ,Research and Analysis Methods ,Infographics ,Mathematical and Statistical Techniques ,Filter Paper ,Image Interpretation, Computer-Assisted ,Computer Science::Multimedia ,Photography ,0202 electrical engineering, electronic engineering, information engineering ,Median filter ,lcsh:Science ,Multidisciplinary ,Pixel ,Data Visualization ,Applied Mathematics ,Simulation and Modeling ,Detector ,lcsh:R ,Digital imaging ,020206 networking & telecommunications ,Salt-and-pepper noise ,White noise ,Filter (signal processing) ,Image Enhancement ,Charts ,Boats ,Laboratory Equipment ,Noise ,Computer Science::Computer Vision and Pattern Recognition ,Physical Sciences ,Engineering and Technology ,020201 artificial intelligence & image processing ,lcsh:Q ,Mathematical Functions ,Algorithm ,Mathematics ,Algorithms ,Research Article - Abstract
In this paper, a two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter is proposed. The first stage firstly detects the noise corrupted pixels by combining characteristic difference parameter and gray level extreme, then develops an improved adaptive median filter to firstly restore them. The second stage introduces a restoration scheme to further restore the noise corrupted pixels, which firstly divides them into two types and then applies different restoration skills for the pixels based on the classification result. One type of pixels is restored by the mean filter and the other type of pixels is restored by the proposed adaptive directional mean filter. The new filter firstly adaptively selects the optimal filtering window and direction template, then replaces the gray level of noise corrupted pixel by the mean value of pixels on the optimal template. Experimental results show that the proposed filter outperforms many existing main filters in terms of noise suppression and detail preservation.
- Published
- 2018