ORTHOGONAL WAVELET DECOMPOSITION WITH MULTI-LEVEL THRESHOLDING FOR IMAGE ENHANCEMENT.

2017 ◽  
Vol 5 (4) ◽  
pp. 1967-1974
Author(s):  
G Kalpana ◽  
◽  
G Karuna ◽  
Keyword(s):  
Image Enhancement ◽  
Wavelet Decomposition ◽  
Orthogonal Wavelet ◽  
Multi Level

scholarly journals 2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys

2012 ◽  
Vol 29 (3) ◽  
pp. 244-250 ◽  
Author(s):  
L. Flöer ◽  
B. Winkel
Keyword(s):  
Image Enhancement ◽  
Image Denoising ◽  
Spectroscopic Data ◽  
Wavelet Decomposition ◽  
Spectroscopic Imaging ◽  
Basic Method ◽  
Spectral Dimension ◽  
Wavelet Coefficients ◽  
Data Cubes ◽  
Spatial Dimensions

AbstractToday, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline.

scholarly journals Framework for comprehensive enhancement of brain tumor images with single-window operation

2020 ◽  
Vol 10 (1) ◽  
pp. 801
Author(s):  
Deepthi Murthy T. S. ◽  
Sadashivappa G.
Keyword(s):  
Brain Tumor ◽  
Image Enhancement ◽  
Medical Image ◽  
Significant Contribution ◽  
Linear Filter ◽  
Radiological Images ◽  
Multi Level ◽  
Image Enhancing ◽  
Non Linear Filter

Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.

Application of Orthogonal Wavelet Decomposition to Plasma Fluctuation Study

1999 ◽  
Vol 38 (Part 2, No. 11B) ◽  
pp. L1345-L1347 ◽  
Author(s):  
Leonid G. Bruskin ◽  
Atsushi Mase ◽  
Yasuyuki Yagi ◽  
Teruo Tamano
Keyword(s):  
Wavelet Decomposition ◽  
Orthogonal Wavelet ◽  
Plasma Fluctuation

Single Image De-Hazing via Multiscale Wavelet Decomposition and Estimation with Fractional Gradient-Anisotropic Diffusion Fusion

2021 ◽  
pp. 2150032
Author(s):  
Uche A. Nnolim
Keyword(s):  
High Frequency ◽  
Anisotropic Diffusion ◽  
Wavelet Decomposition ◽  
Single Image ◽  
Nonlocal Means ◽  
Gradient Domain ◽  
Multi Level ◽  
Bilateral Filters ◽  
Approximation Coefficients ◽  
Experimental Comparisons

This paper presents algorithms based on fractional multiscale gradient fusion and multilevel wavelet decomposition for underwater and hazy image enhancement. The algorithms utilize partial differential equation (PDE)-generated low- and high-frequency images fused via gradient domain and anisotropic diffusion. Furthermore, wavelet multi-level decomposition, estimation and adjustment of detail and approximation coefficients are employed in improving local and global enhancement. Solutions to halo effect are also developed using compressive bilateral filters or other nonlinear/nonlocal means filter. Ultimately, experimental comparisons indicate that the proposed methods surpass or are comparable to several algorithms from the literature.

Sign in / Sign up

Export Citation Format

Share Document