scholarly journals A robust quasi-Newton adaptive filtering algorithm for impulse noise suppression

2002 ◽  
Author(s):  
Yuexian Zou ◽  
Shing-Chow Chan
Keyword(s):  
Adaptive Filtering ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Filtering Algorithm ◽  
Quasi Newton

Improved Quasi-Newton Adaptive-Filtering Algorithm

2010 ◽  
Vol 57 (8) ◽  
pp. 2109-2118 ◽  
Author(s):  
Md Zulfiquar Ali Bhotto ◽  
Andreas Antoniou
Keyword(s):  
Adaptive Filtering ◽  
Filtering Algorithm ◽  
Quasi Newton

A fast quasi-Newton adaptive filtering algorithm

1992 ◽  
Vol 40 (7) ◽  
pp. 1652-1662 ◽  
Author(s):  
D.F. Marshall ◽  
W.K. Jenkins
Keyword(s):  
Adaptive Filtering ◽  
Filtering Algorithm ◽  
Quasi Newton

FPGA-Based Re-Configurable Architecture for Window-Based Image Processing

2018 ◽  
pp. 273-310
Author(s):  
Kamarujjaman Sk ◽  
Manali Mukherjee ◽  
Mausumi Maitra
Keyword(s):  
Adaptive Filtering ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Digital Images ◽  
Median Filter ◽  
Hardware Architecture ◽  
Efficient Design ◽  
Filtering Method ◽  
Switching Median Filter ◽  
Noise Density

In this proposed book chapter, a simple but efficient presentation of Median Filter, Switching Median Filter, Adaptive Median Filter and Decision-Based Adaptive Filtering Method and their hardware architecture for FPGA is described for removal of up to 99% impulse noise from Digital Images. For hardware architecture, simulation is done using Xilinx ISE 14.5 software of XILINX. For implementation, these approaches utilize Genesys VIRTEX V FPGA device of XC5VLX50T device family. In this approach, we proposed an efficient design for suppression of impulse noise from digital images corrupted by up to 99% impulse noise using decision based adaptive filtering method as well as preserve the details of image. The method works in two different stages – noise detection using switching technique and finally noise suppression and restoration. Experimental results show that our method perform better in terms of PSNR below 80% noise density but above 80% noise density it is almost comparable with the latest methods.

FPGA-Based Re-Configurable Architecture for Window-Based Image Processing

2017 ◽  
pp. 1-46
Author(s):  
Kamarujjaman Sk ◽  
Manali Mukherjee ◽  
Mausumi Maitra
Keyword(s):  
Adaptive Filtering ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Digital Images ◽  
Median Filter ◽  
Hardware Architecture ◽  
Efficient Design ◽  
Filtering Method ◽  
Switching Median Filter ◽  
Noise Density

In this proposed book chapter, a simple but efficient presentation of Median Filter, Switching Median Filter, Adaptive Median Filter and Decision-Based Adaptive Filtering Method and their hardware architecture for FPGA is described for removal of up to 99% impulse noise from Digital Images. For hardware architecture, simulation is done using Xilinx ISE 14.5 software of XILINX. For implementation, these approaches utilize Genesys VIRTEX V FPGA device of XC5VLX50T device family. In this approach, we proposed an efficient design for suppression of impulse noise from digital images corrupted by up to 99% impulse noise using decision based adaptive filtering method as well as preserve the details of image. The method works in two different stages – noise detection using switching technique and finally noise suppression and restoration. Experimental results show that our method perform better in terms of PSNR below 80% noise density but above 80% noise density it is almost comparable with the latest methods.

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