Correspondences between Wavelet Shrinkage and Nonlinear Diffusion

Nonlinear diffusion filtering and wavelet shrinkage are two successfully applied methods for discontinuity preserving denoising of signals and images. Recently, relations between both methods have been established taking into account wavelet shrinkage at one scale. In this paper, we propose a new explicit scheme for nonlinear diffusion which directly incorporates ideas from multiscale Haar wavelet shrinkage. We prove that our scheme permits larger time steps while preserving convergence to the mean signal value. Numerical examples demonstrate the behavior of our scheme for two and three scales.

Download Full-text

RELATIONS BETWEEN WAVELET SHRINKAGE AND NONLINEAR DIFFUSION IN IMAGE DENOISING

Wavelet Analysis and Active Media Technology ◽

10.1142/9789812701695_0194 ◽

2005 ◽

pp. 1254-1259

Author(s):

YADONG WU ◽

YONGHUI CHEN ◽

SHIXIN SUN

Keyword(s):

Image Denoising ◽

Nonlinear Diffusion ◽

Wavelet Shrinkage

Download Full-text

A MULTISCALE TIGHT FRAME-INSPIRED SCHEME FOR NONLINEAR DIFFUSION

International Journal of Wavelets Multiresolution and Information Processing ◽

10.1142/s0219691312500415 ◽

2012 ◽

Vol 10 (05) ◽

pp. 1250041 ◽

Cited By ~ 2

Author(s):

HAIHUI WANG ◽

XIAO KONG

Keyword(s):

Nonlinear Diffusion ◽

Tight Frame ◽

Wavelet Shrinkage ◽

Numerical Examples ◽

Spatial Level ◽

One Step ◽

Shrinkage Functions

Nonlinear diffusion and wavelet shrinkage are two successfully applied methods for discontinuity preserving denoising of signals and images. Recently, relations between both methods have been established taking into account wavelet shrinkage at one or multiscale. In this paper we show that one step of (stabilized) explicit discretization of nonlinear diffusion can be expressed in terms of tight frame shrinkage on a single spatial level or multiscale. We prove that our scheme permits larger steps while having more choices of shrinkage functions. Numerical examples demonstrate the behavior of our scheme for one or two scales.

Download Full-text

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.21 ◽

2017 ◽

Vol 7 (8) ◽

pp. 56

Author(s):

Ashish Dwivedi ◽

Nirupma Tiwari

Keyword(s):

Image Enhancement ◽

Color Image ◽

Human Perception ◽

Histogram Equalization ◽

Wavelet Shrinkage ◽

Visual Appearance ◽

Enhancement Method ◽

Fuzzy Histogram ◽

Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

Download Full-text