INTEGRATION OF WAVELET AND HUFFMAN COMPRESSION MECHANISM TO IMPROVE SECURITY WITH FINE IMAGE QUALITY
Keywords:
Image Compression, Huffman, Wavelet Mechanism, Mean square errorAbstract
Nowadays, there is the requirement of a mechanism which can compress the graphical content without decreasing the quality of image. Therefore, wavelet mechanism has been integrated with Huffman mechanism. These two compression mechanisms are integrated and used to increase the compression ratio and decrease the image size. The content has been compressed as dual layer. Huffman compression has been used on first layer and wavelet mechanism has been used to compress the content at second layer. Two performance parameters are considered to measure the performance of graphical content compression algorithm. The considered parameters are Peak Signal to Noise Ratio and Mean square error. In the research work, the comparison between traditional wavelet based and Huffman based image compression with proposed algorithm is proposed. The proposed integration is beneficial to compress the data without losing its quality.
References
Khan, Umhara & Mairaj, Sanna & Nazeer, Tamanna & Ahmed, Suhaib. (2017). Wavelet Based graphical content Compression Mechanisms: Comparative Analysis & Performance Evaluation. International Journal of Emerging Technologies in Engineering Research. 5. 9-13.
Nedhal Mohammad Al-Shereefi “Image Compression Using Wavelet Transform “ Babylon University/Collage of Science/Department of Physics,Journal of Babylon University/Pure & Applied Sciences/ No.(4)/ Vol.(21): 2013
Rachit Patel ,Virendra Kumar “A Fast & Improved graphical content Compression mechanism U sing Huffman Coding “This fUll-text paper was peer-reviewed & accepted to be presented at IEEE WiSPNET 2016 conference.
Marcus J. Nadenau & Julien Reichel (1997) “Opponent Color, Human Vision & Wavelets for graphical content Compression”
Hidenori Sakanashi, Mehrdad Salami (1998) “Evolvable Hardware Chip for High Precision Printer graphical content Compression”
M. Klimesh, V. Stanton, & D. Watola (2001) “Hardware Implementation of a Lossless graphical content Compression Algorithm Using a Field Programmable Gate Array”
M Saenz, P Salama, K Shen (2001) “An Evaluation of Color Embedded Wavelet graphical content Compression Mechanisms”
William A. Pearlman(2002) “Trends of Tree-Based, Set-Partitioning Compression Mechanisms in Still & Moving graphical content Systems”
Anna Linderhed (2004) “Image Compression based on Empirical Mode Decomposition”
John Kominek(2006) “Algorithm for Fast Fractal graphical content Compression”
Matthew J. Zukoski (2006) “A novel approach to medical graphical content compression” Int. J. Bioinformatics Research & Applications, Vol. 2, No. 1, 2006
P. Raviraj & 2M.Y. Sanavullah(2007) “The Modified 2D-Haar Wavelet Transformation in graphical content Compression” Middle-East Journal of Scientific Research 2 (2): 73-78, 2007
Ahmed Nabil belbachir & Peter Michael(2010) “The Contour let Transform For graphical content Compression”
David Varodayan, Anne Aaron, & Bernd Girod (2010) “Exploiting Spatial Correlation in Pixel-Domain Distributed graphical content Compression”
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