Reconfigurable architecture of adaptive median filter – an fpga based approach for impulse noise suppression || 2015-2016 IEEE Matlab Projects

1. Reconfigurable Architecture of Adaptive
Median Filter – An FPGA Based Approach for
Impulse Noise Suppression
Presented by
IIS TECHNOLOGIES
No: 40, C-Block,First Floor,HIET Campus,
North Parade Road,St.Thomas Mount,
Chennai, Tamil Nadu 600016.
Landline:044 4263 7391,mob:9952077540.
Email:info@iistechnologies.in,
Web:www.iistechnologies.in
www.iistechnologies.in

2. ABSTRACT
• In this paper, low complexity reconfigurable hardware architecture for adaptive median filter is
proposed and a comparative study of hardware based median and adaptive median filter is
presented. An efficient development of median & adaptive median filter is presented for removal
of impulse noise mainly salt & pepper noise from digital Images.
• Performance measurement of mean square error (MSE) and peak signal-to-noise ratio (PSNR) is
done to compare these two filters. This paper proposes hardware implementation which is highly
required for real time execution.
• Field Programmable Gate Arrays (FPGAs) are widely used for real time processing where the
requirements of time, speed, area, power become strict. The algorithms of these two filters are
discussed in detail which is followed by FPGA based solutions. Simulation is done using Xilinx ISE
14.5 software of XILINX platform where the implementations utilize on Genesys VERTEX V FPGA
Board of XC5VLX50T device family.
• Keywords--Adaptive Median Filter, Median Filter, Real-time Filtering, Salt-and-pepper noise,
Impulse Noise, Field programmable gate array (FPGA).
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3. Introduction of the Median Filter
• The field of image processing has wide and important uses. Any field of work that involves images or
videos has uses for research in this area. The results of this project will influence how images are
processed and enhanced.
• Application stemming from the results of this project will be important to image and video
enhancement applications because this research project provides insights on the best techniques in
filtering and enhancing each kind of image.
• This project explores the effects of the median filter on different types of images. The fields explored
include its effects on digital images of people, scenery, and objects. The quality of filtered images will
be determined in a subjective manner.
• The effects of human errors and subjectivity do not detract from this study because image filtering is
done for subjective and aesthetic qualities, so this method of evaluation makes sense as well. The
median filter considers each pixel in the image in turn and looks at its nearby neighbors to decide
whether or not it is representative of its surroundings.
• Instead of simply replacing the pixel value with the mean of neighboring pixel values, it replaces it with
the median of those values. The median is calculated by first sorting all the pixel values from the
surrounding neighborhood into numerical order and then replacing the pixel being considered with the
middle pixel value.
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4. PROPOSED METHOD
The proposed system is developed in order to get the following
• Input size is varied and results are analyzed
• Gray code input is given and their results are analyzed
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5. Advantages of the PROPOSED METHOD
• The advantage of the proposed system is having such that the newly developed algorithm is
having low delay than the existing system.
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6. Block Diagram
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7. Flowchart
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8. TOOLS AND SOFTWARE USED
• Simulation Tool : Model-Sum 6.3c
• Synthesis Tool : Xilinx ISE 12.1
• Image Processing Tool : MATLAB 2010
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9. Reference
• [1] Rafael C. Gonzalez, and Richard E. woods, Digital Image Processing, 3rd
edition, Prentice Hall, 2009.
• [2] W.K. Pratt, Digital Image Processing. Wiley-Interscience, 1991
• [3] H. Hwang and R.A. Haddad, Adaptive Median Filters: New Algorithms and
Results, IEEE Trans. Image Processing, vol. 4, no. 4, pp. 499 - 502, Apr. 1995
• [4] S. Zhang and M.A. Karim, A New Impulse Detector for Switching Median Filter,
IEEE Signal Processing Letters, vol. 9, no. 11, pp. 360-363, Nov. 2002
• [5] R.H. Chan, C.W. Ho, and M. Nikolova, Salt-and-Pepper Noise Removal by
Median-Type Noise Detectors and Detail-Preserving Regularization, IEEE Trans.
Image Processing, vol. 14, no. 10, pp. 1479-1485, Oct. 2005
• [6] P.E. Ng and K.K. Ma, A Switching Median Filter with Boundary Discriminative
Noise Detection for Extremely Corrupted Images, IEEE Trans. Image Processing,
vol. 15, no. 6, pp. 1506-1516, June 2006
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10. OUTPUT
• SIMULATION
• HARDWARE
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11. Contact
IIS TECHNOLOGIES
No: 40, C-Block,First Floor,HIET Campus,
North Parade Road,St.Thomas Mount,
Chennai, Tamil Nadu 600016.
Landline:044 4263 7391,mob:9952077540.
Email:info@iistechnologies.in,
Web:www.iistechnologies.in
www.iistechnologies.in