Title :
The K Nearest Neighbor Geometry Filter Based on Spatial Domain
Author :
Wang Nizhuan ; Zeng Weiming
Author_Institution :
Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China
Abstract :
Based on the filter using the K nearest neighbor pixels and geometric mean grayscale value method, a derived image denoising algorithm is proposed in this paper. This approach firstly searches K-l nearest grayscale neighbors of a central pixel covered by the mask. Then it calculates geometric mean gray value of the K pixels including the k-l neighbors and the central pixel. Lastly, replaces the grayscale value of the central pixel with the geometric gray value. Experiment results show the proposed method has better performance on the mixed noise suppression in comparison to the classical Mean filter, the standard median filter and the KNN mean filter.
Keywords :
image denoising; median filters; K nearest neighbor geometry filter; K nearest neighbor pixels; K-l nearest grayscale neighbors; KNN mean filter; central pixel; geometric mean grayscale value method; image denoising algorithm; median filter; mixed noise suppression; spatial domain; Filtering theory; Geometry; Maximum likelihood detection; Nearest neighbor searches; Noise; Nonlinear filters; Pixel;
Conference_Titel :
Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5088-6
DOI :
10.1109/icbbe.2011.5780368