No Current Issue
A Comparison of Image Denoising Methods using Wavelet, Contour let and Curve let Multi Resolution Transforms
Image Processing is any form of signal processing for which the input is an image or video frame; the output of image processing is set of parameters related to the image. The goal of our research presents Denoising using various multi-resolution transforms (MRA) such as wavelets, Contourlets and Curvelets. Curvelet based image denoising method is compared with Wavelet denoising and contourlet denoises. The analysis shows that Curvelet performs better than wavelet and contourlet because the no. of co-efficient needed to represent a curve is lesser in Curvelet than Contour let and then Wavelet. Hence the computational complexity has also been reduced when using Curvelet transform.
Multi Resolution Analysis, Fourier Transform, Gaussian Scale Mixture, Wavelet Transform, Contourlet Transform, Curvelet Transform.
Copyright © 2013-2026 ERES Publications