TY  - JOUR
T1  - Additive Noise Removal for Color Images using Wavelet Based Fuzzy Filter
AU - Mythili, C. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 4
SP  - 833
EP  - 839
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.833.839
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.833.839
KW  - Median
KW  -wiener
KW  -fuzzy filter
KW  -wavelet based fuzzy filter
KW  -peak signal to noise ratio
KW  -SSIM
AB  - Noise removal is an important step for an image retrieval system to remove the unwanted information present in the image using filtering techniques for web based applications. Web images are often degraded by additive noise. The goal of smoothing the image is to remove the noise while retaining the image features such as color, texture, shape and so on. The denoising technique yields a better quality image. Denoising can be done through filtering which can either be linear filtering or non-linear filtering. Linear filters do not eliminate additive noise as they have a tendency to blur the edges of an image. On the other hand, nonlinear filter is suitable for dealing with additive noise. These filters operate on small size windows and replace the value of the central pixel. Compared to other nonlinear techniques, wavelet based fuzzy filters have the ability to combine edge preservation and smoothing. In this study, wavelet based fuzzy filter is used to filter the images and the result proved better in terms of Peak Signal to Noise Ratio (PSNR) and Structural SI Milarity (SSIM) when compared other filters.
ER  -