Title :
Technique for mixed noise reduction based on support vector machine [image denoising]
Author :
Fujiki, Amanda ; Matsushita, J. ; Imai, Tetsuro ; Muneyasu, Mitsuji
Author_Institution :
Kansai Univ., Osaka, Japan
Abstract :
Summary form only given. In this paper, we propose a new noise reduction method for images based on support vector machines (SVM). This method classifies pixels by their local features and processes them by a suitable method according to their features. In the proposed method, white Gaussian noise reduction with edge preservation is especially considered. The mixed noise reduction technique, based on a combination of the proposed method and an impulse noise reduction filter by using the SVM, is also described. Simulation results show the effectiveness of the proposed method for the reduction of white Gaussian noise and mixed noise with edge preservation.
Keywords :
Gaussian noise; image denoising; impulse noise; support vector machines; SVM; edge preservation; image denoising; impulse noise reduction filter; mixed noise reduction; pixel local feature classification; support vector machines; white Gaussian noise reduction; Additive noise; Analysis of variance; Filters; Gaussian noise; Noise reduction; Speckle; Support vector machine classification; Support vector machines; Wavelet analysis; Wavelet transforms;
Conference_Titel :
Nonlinear Signal and Image Processing, 2005. NSIP 2005. Abstracts. IEEE-Eurasip
Conference_Location :
Sapporo
Print_ISBN :
0-7803-9064-4
DOI :
10.1109/NSIP.2005.1502256