A novel algorithm of image denoising based on the grey absolute relational analysis

2009 ◽  
Author(s):  
Gang Li ◽  
Xinping Xiao ◽  
Yufeng Gui
Keyword(s):  
Image Denoising ◽  
Relational Analysis ◽  
Novel Algorithm

scholarly journals A Novel Algorithm for Image Denoising Using DT-CWT

2017 ◽  
Vol 8 (3) ◽  
pp. 15-29
Author(s):  
SK.Umar Faruq ◽  
Ramanaiah K.V. ◽  
Soundararajan K.
Keyword(s):  
Image Denoising ◽  
Novel Algorithm

scholarly journals From Insect Vision to a Novel Bio-Inspired Algorithm for Image Denoising

2020 ◽  
Author(s):  
Manfred Hartbauer
Keyword(s):  
Image Denoising ◽  
Color Images ◽  
Insect Vision ◽  
Night Vision ◽  
Primitive Type ◽  
Noise Estimate ◽  
Local Means ◽  
Static Images ◽  
Image Details ◽  
Novel Algorithm

Night active insects inspired the development of image enhancement methods that uncover the information contained in dim images or movies. Here, I describe a novel bionic night vision (NV) algorithm that operates in the spatial domain to remove noise from static images. The parameters of this NV algorithm can be automatically derived from global image statistics and a primitive type of noise estimate. In a first step, luminance values were ln-transformed, and then adaptive local means’ calculations were executed to remove the remaining noise without degrading fine image details and object contours. Its performance is comparable with several popular denoising methods and can be applied to grey-scale and color images. This novel algorithm can be executed in parallel at the level of pixels on programmable hardware.

A Novel Algorithm for Generalized Image Denoising Using Dual Tree Complex Wavelet Transform

2012 ◽  
Vol 7 (2) ◽  
pp. 24-33
Author(s):  
S.K. Umar Faruq ◽  
◽  
K.V. Ramanaiah ◽  
K. Soundara Rajan ◽  
◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Complex Wavelet Transform ◽  
Complex Wavelet ◽  
Novel Algorithm

Software solution of medical grey relational method based on SAS environment

2016 ◽  
Vol 6 (3) ◽  
pp. 309-321 ◽  
Author(s):  
Jin-Xiu Zhu ◽  
Xue-Rui Tan ◽  
Nan Lu ◽  
Shao-Xing Chen ◽  
Xiao-Jun Chen
Keyword(s):  
Original Data ◽  
Reference Sequence ◽  
The Novel ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Typical Distribution ◽  
Grey Relational Coefficient ◽  
Grey Relational ◽  
Novel Algorithm

Purpose The purpose of this paper is to construct a new algorithm of program procedure for medical grey relational method based on SAS software. Design/methodology/approach Based on the SAS environment, the authors construct a new algorithm of program procedure through the following methods: the construction data set, confirmation of the comparison sequence and reference sequence, the original data transformation, calculation of the grey relational coefficient of reference sequence and comparison sequence and calculating the correlation. Findings The results show that the novel algorithm of program procedure for medical grey relational method based on SAS software satisfies the properties properly. It also fully confirmed the biggest advantage of the grey relational analysis is that its requirements are not too high for the amount of data, and it does not need to follow the typical distribution. Originality/value The paper succeeds in constructing a novel algorithm of program procedures for medical grey relational method and providing a valuable tool for solving similar problems.

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