Title :
A Tristate Approach Based on Weighted Mean and Backward Iteration
Author :
Ma, Yanhua ; Liu, Chuanjun ; Sun, Haiying
Author_Institution :
Qingdao Univ. of Sci. & Technol., Qingdao
fDate :
July 30 2007-Aug. 1 2007
Abstract :
A tristate approach (TA) for image denoising processing is presented; the noise is aimed at the presence of pepper-and-salt noise. The newness of this method is that it develops a new route in the field of image restoration. The tristate approach algorithm focuses on the removal and restoration of the noisy speckles and avoids blurring and averaging edges and non-noise pixels in a way different from other known algorithms. Any noisy pixel is replaced by an estimated value. This value is the weighted mean of the pixels neighboring to the noisy pixel or the four iteration pixels got before it. This paper describes, analyzes and compares several methods and results of removing noise from an image. We have performed the experiments by adding Salt-and-Pepper in an original image.
Keywords :
image denoising; image restoration; backward iteration; image denoising; image restoration; noisy speckles; nonnoise pixels; pepper-and-salt noise; tristate approach; weighted mean; Degradation; Educational institutions; Filtering; Image denoising; Image restoration; Information science; Maximum likelihood detection; Nonlinear filters; Pixel; Smoothing methods; image denoising; noisy density.; pepper-and-salt noise; tristate approach;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-0-7695-2909-7
DOI :
10.1109/SNPD.2007.338