The Choice of Filter Parameters for Non-Linear Grey-Value Image Processing

1986 ◽  
Author(s):  
A. Beckers ◽  
L. Dorst ◽  
I. T. Young
Keyword(s):  
Image Processing ◽  
Non Linear

Application of non-linear transform coding to image processing

2012 ◽  
Author(s):  
Jens Hocke ◽  
Erhardt Barth ◽  
Thomas Martinetz
Keyword(s):  
Image Processing ◽  
Transform Coding ◽  
Non Linear ◽  
Linear Transform

The Applicability of Neural Networks to Non-linear Image Processing

1999 ◽  
Vol 2 (2) ◽  
pp. 111-128 ◽  
Author(s):  
D. de Ridder ◽  
R.P.W. Duin ◽  
P.W. Verbeek ◽  
L.J. van Vliet
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Non Linear

scholarly journals A Proposed Non Linear Block Based Approach for Image De-Noising Using Wavelet

2013 ◽  
Vol 5 (3) ◽  
pp. 226-231
Author(s):  
Tajinder Singh ◽  
Rajeev Bedi ◽  
S.K Gupta
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Processing System ◽  
Noise Power ◽  
Blocking Artifacts ◽  
Linear Threshold ◽  
Non Linear ◽  
Real Time Applications ◽  
Block Based

Coding of images or processing of images has played a momentous role in the success of digital communications and multimedia. Coding plays a major role is 3D mobile generation. The image processing methods have been exploited through the years to improve the quality of digital images. In the image processing system De-noising based coding is used extensively. As we know that, in low bit rate applications, the blocking artifacts problem arises, which severely reduce the visual quality of the image. Reducing blocking artifacts is essential to render the compressed visual data acceptable to the viewer. So, to detect and reduce noise from the image is a major task. So removing the noise from original signal is still a challenging problem for researchers. There have been several published algorithms and each approach has its assumptions, advantages, and limitations. For real-time applications like television, photo-phone, etc. it is essential to reduce the noise power as much as possible and to retain the fine details and the edges in the image as well. Moreover, it is very important to have very low computational complexity so that the filtering operation is performed in a short time for online and real-time applications. The main focus of this paper is first to define an algorithm and based on that a non linear threshold filter is described which not only preserve the actual image structures in the presence of different types of noises (Salt & peepers, Speckle and Gaussian Noise) as well as it provide better  PSNR, MSE, MAE, & Time Complexity than others Classical algorithms.

scholarly journals Non Linear Image Processing with Evolvable Hardware Filter

2011 ◽  
Vol 3 (8) ◽  
pp. 227-230
Author(s):  
Syed Jahangir Badashah ◽  
◽  
Dr. P. Subbaiah Dr. P. Subbaiah
Keyword(s):  
Image Processing ◽  
Evolvable Hardware ◽  
Non Linear
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