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Algorithm for lossy image compression using FPGA

05 Apr 2013  | K. Rajesh Kumar

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Given a noise-free m×n monochrome image I and its noisy approximation K, MSE is defined as:


The MSE of the proposed algorithm is 0.0038910(signal iteration).

Figure 6: MSE comparison.



Mean-square signal to noise ratio SNRms
The f (x,y) is the input image and the f^ (x,y) is the compressed image where as M and N are the rows and column of the matrix.


The SNRms of the proposed algorithm is 1.


PSNR
The PSNR is a measure of the peak error.

The PSNR is defined as:


Here, MAXI is the maximum possible pixel value of the image

The PSNR of the proposed algorithm is 1.1090355e+002.

Figure 7: Surface plot of original image.


Figure 8: Surface plot of compressed image.


Figures 7 and 8 show the surface plot of original and compressed images. The Z-Axis of original image is weighted upto 253, where as the compressed image maximum weight is 1.


Conclusion
In this paper, we have proposed a noval algorithm and compared it with the standard LMS, the normalized LMS (NLMS),the MVSS, the conventional TDLMS, the DCT-LMS, the TDVSS, and the VSSTDLMS. With the proposed algorithm, when the number of iteration increases the MSE and the resolution reduces, and the lookup table (threshold pool) size increases. From the figure 6, we can justify that the proposed algorithm is better than LMS, NLMS and MVS in terms of MSE.


Reference
1. Tyseer Aboulnasr, and K. Mayyas , "A Robust Variable Step-Size LMS-Type Algorithm: Analysis and Simulations" , IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 45, NO. 3, MARCH 1997

2. S.SHANKAR NARAYAN, ALLEN M. PETERSON and MADIHALLY J. NARASIMHA, "Transform Domain LMS Algorithm" , IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL. ASSP-31, NO. 3, JUNE 1983

3. K. Mayyas , Irbid and Jordan ,a note on "Performance analysis of the DCT-LMS adaptive filtering algorithm", journal, signal processing volume 85 issue 7 July 2005

4. Radu Ciprian Bilcu, Pauli Kuosmanen, and Karen Egiazarian , "A Transform Domain LMS Adaptive Filter With Variable Step-Size" , IEEE SIGNAL PROCESSING LETTERS, VOL. 9, NO. 2, FEBRUARY 2002

5. K. Mayyas , "Mean-Square Analysis of a Variable Step She Transform Domain LMS Adaptive Algorithm"

6. Zhao Shengkui, Man Zhihong and Khoo Suiyang, "A New Variable Step-Size Transform Domain LMS Algorithm with System Identification", IEEE International Conference on Control and Automation Guangzhou, CHINA—May 30 to June 1, 2007

7. K. Mayyas, "A transform domain LMS algorithm with an adaptive stepsize equation," The 4th IEEE International Symposium on Signal Processing and Information Technology ISSPIT' 2004, Italy, Rome,Dec. 28-30, 2004.


About the author
K.Rajesh Kumar received M.tech in VLSI design from Karunya University in 2011 and B.E in Electronics and Communication Engineering from Anna University. He finished Diploma in Electronics and Communication Engineering in 2006 and subsequently did Diploma in Information Technology and Advanced Diploma in Information Technology in 2005. He is currently working with Mistral Solutions as a Design Engineer. He has published various papers in national and international journals. He has successfully completed many projects in Image Broadcasting and video processing. His research interest includes Image Compression, Low power VLSI and Cryptography.


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