Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007) A Tristate Approach Based on Weighted Mean and Backward Iteration Haier International Training Center, Qingdao, China July 30-August 01 ISBN: 0-7695-2909-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.338
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.
Index Terms:
image denoising, tristate approach, pepper-and-salt noise, noisy density.
Citation:
Yanhua Ma, Chuanjun Liu, Haiying Sun, "A Tristate Approach Based on Weighted Mean and Backward Iteration," snpd, vol. 2, pp.616-621, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||