Log in

Relevant bibliographies by topics / VisuShrink

Contents

Journal articles

Academic literature on the topic 'VisuShrink'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'VisuShrink.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "VisuShrink"

1

Chaabouni, Imen, Wiem Fourati, and M. Salim Bouhlel. "Visushrink Pretreatment for Image Compression." International Journal of Computer Applications 23, no. 6 (2011): 10–16. http://dx.doi.org/10.5120/2893-3785.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Chikanbanjar, Milan. "Comparative analysis between non-linear wavelet based image denoising techniques." Journal of Science and Engineering 5 (August 31, 2018): 58–67. http://dx.doi.org/10.3126/jsce.v5i0.22373.

Full text

Abstract:

Digital images have been a major form of transmission of visual information, but due to the presence of noise, the image gets corrupted. Thus, processing of the received image needs to be done before being used in an application. Denoising of image involves data manipulation to remove noise in order to produce a good quality image retaining different details. Quantitative measures have been used to show the improvement in the quality of the restored image by the use of various thresholding techniques by the use of parameters mainly, MSE (Mean Square Error), PSNR (Peak-Signal-to-Noise-Ratio) an

APA, Harvard, Vancouver, ISO, and other styles

3

Xie, Wendi, Yurong Zhao, and Yang Wang. "Research on Wavelet Transform Technology and Image Processing Performance Based on Matlab." Journal of Physics: Conference Series 2031, no. 1 (2021): 012007. http://dx.doi.org/10.1088/1742-6596/2031/1/012007.

Full text

Abstract:

Abstract This paper first introduces the basic concept, principle and application of wavelet transform. Then, the performance characteristics of Haar wavelet, dbN wavelet and symN wavelet, two different threshold shrinkage algorithms Visushrink and Bayesshrink, and two common threshold functions are described in detail. Finally, Matlab software programming is used to realize the simulation of the original image based on different wavelet bases in the influence of Gaussian noise, Poisson noise and salt and pepper noise, different threshold acquisition algorithm, different threshold function, an

APA, Harvard, Vancouver, ISO, and other styles

4

CHEN, GUANGYI, TIEN D. BUI, and ADAM KRZYZAK. "DENOISING OF THREE-DIMENSIONAL DATA CUBE USING BIVARIATE WAVELET SHRINKING." International Journal of Pattern Recognition and Artificial Intelligence 25, no. 03 (2011): 403–13. http://dx.doi.org/10.1142/s0218001411008725.

Full text

Abstract:

The denoising of a natural signal/image corrupted by Gaussian white noise is a classical problem in signal/image processing. However, it is still in its infancy to denoise high dimensional data. In this paper, we extended Sendur and Selesnick's bivariate wavelet thresholding from two-dimensional (2D) image denoising to three-dimensional (3D) data cube denoising. Our study shows that bivariate wavelet thresholding is still valid for 3D data cubes. Experimental results show that bivariate wavelet thresholding on 3D data cube is better than performing 2D bivariate wavelet thresholding on every sp

APA, Harvard, Vancouver, ISO, and other styles

5

Golkar Amoli, Mehdi, Mahdi Hasanlou, Ruhollah Taghizadeh Mehrjardi, and Farhad Samadzadegan. "Exploring the Potential of PRISMA Satellite Hyperspectral Image for Estimating Soil Organic Carbon in Marvdasht Region, Southern Iran." Remote Sensing 16, no. 12 (2024): 2149. http://dx.doi.org/10.3390/rs16122149.

Full text

Abstract:

Soil organic carbon (SOC) is a crucial factor for soil fertility, directly impacting agricultural yields and ensuring food security. In recent years, remote sensing (RS) technology has been highly recommended as an efficient tool for producing SOC maps. The PRISMA hyperspectral satellite was used in this research to predict the SOC map in Fars province, located in southern Iran. The main purpose of this research is to investigate the capabilities of the PRISMA satellite in estimating SOC and examine hyperspectral processing techniques for improving SOC estimation accuracy. To this end, denoisi

APA, Harvard, Vancouver, ISO, and other styles

6

Nasar, Iqbal. "Reduction of Noise from Fingerprint Images using Stationary Wavelet Trasnform." International Journal of Engineering Works (ISSN: 2409-277) 4, no. 12 (2017): 104–8. https://doi.org/10.5281/zenodo.1133286.

Full text

Abstract:

In Automatic Fingerprint Identification Systems (AFIS) the quality of image is a very important factor as the minutiae extraction from fingerprint image heavily depends on image quality. To enhance the quality of fingerprint images a large number of denoising methods has been used. In this paper fingerprint image enhancement using stationary wavelet transform has been analyzed using different wavelets with different thresholds. Four different wavelets namely Haar DB4 (Daubechies), Coif2 (Coilflets) and Bior1.3 (Biorthogonal) were selected with four thresholds namely VisuShrink, NormalShrink, N

APA, Harvard, Vancouver, ISO, and other styles

7

Kumar, Sushil. "DT-CWT Based Block Nonlinear De-Noising." International Journal of Advance Research and Innovation 4, no. 2 (2016): 6–13. http://dx.doi.org/10.51976/ijari.421602.

Full text

Abstract:

For image denoising, Block thresholding is considered to be a better strategy than the term-by-term thresholding. There are number of Wavelet based thresholding techniques for image denoising such as VisuShrink, BayesShrink, SureShrink, NeighShrink, BiShrink, ProbShrink, Sure-LET and BlockShrink. Selesnick has extended the BiShrink method to DT-CWT and he has shown that the DT-CWT achieves better results than DWT for image denoising. Dengwen and Xiaoliu have shown that BlockShrink enjoys a number of advantages over the other conventional image denoising methods. Their experimental results show

APA, Harvard, Vancouver, ISO, and other styles

8

Nisha, S. Shajun, and S. P. Raja. "Multiscale Transform and Shrinkage Thresholding Techniques for Medical Image Denoising – Performance Evaluation." Cybernetics and Information Technologies 20, no. 3 (2020): 130–46. http://dx.doi.org/10.2478/cait-2020-0033.

Full text

Abstract:

AbstractDue to sparsity and multiresolution properties, Mutiscale transforms are gaining popularity in the field of medical image denoising. This paper empirically evaluates different Mutiscale transform approaches such as Wavelet, Bandelet, Ridgelet, Contourlet, and Curvelet for image denoising. The image to be denoised first undergoes decomposition and then the thresholding is applied to its coefficients. This paper also deals with basic shrinkage thresholding techniques such Visushrink, Sureshrink, Neighshrink, Bayeshrink, Normalshrink and Neighsureshrink to determine the best one for image

APA, Harvard, Vancouver, ISO, and other styles

9

Seetharaman, R., M. Tharun, and K. Anandan. "A Novel approach in Hybrid Median Filtering for Denoising Medical images." IOP Conference Series: Materials Science and Engineering 1187, no. 1 (2021): 012028. http://dx.doi.org/10.1088/1757-899x/1187/1/012028.

Full text

Abstract:

Abstract Image denoising is a key pre-processing step in medical image analysis. At current, deep learning-based models have shown a great promise, which outperformed many conventional methods over the past three decades. Speckle noise removal is a major issue in preserving all the delicate details and the edges in ultrasound image processing as it degrades the visual evaluation of ultrasound images. The multiplicative behavior of speckle-noise is converted into additive by using log transform as the additive noise removal is easy as compared to multiplicative noise. An innovative approach for

APA, Harvard, Vancouver, ISO, and other styles

10

Gong, Tierui, Zhijia Yang, Gengshan Wang, and Ping Jiao. "Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function." Mathematical Problems in Engineering 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/5203214.

Full text

Abstract:

Unlike inflexible structure of soft and hard threshold function, a unified linear matrix form with flexible structure for threshold function is proposed. Based on the unified linear flexible structure threshold function, both supervised and unsupervised subband adaptive denoising frameworks are established. To determine flexible coefficients, a direct mean-square error (MSE) minimization is conducted in supervised denoising while Stein’s unbiased risk estimate as a MSE estimate is minimized in unsupervised denoising. The SURE rule requires no hypotheses or a priori knowledge about clean signal

APA, Harvard, Vancouver, ISO, and other styles

More sources

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!