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Gray-Scale Image Compression Techniques: A Review
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 13 |
| Year of Publication: 2015 |
| Authors: Asawari Kulkarni, Aparna Junnarkar |
10.5120/ijca2015907519
|
Asawari Kulkarni, Aparna Junnarkar . Gray-Scale Image Compression Techniques: A Review. International Journal of Computer Applications. 131, 13 ( December 2015), 22-25. DOI=10.5120/ijca2015907519
Abstract
Multimedia data are large in size as compared to the plain-text data. And hence to transmit them over a low-bandwidth communication channel, it needs to be compressed. In this paper, focus is on compressing gray-scale images. Here two types of compression techniques are explained: Lossy and Lossless. Within lossy techniques, there are three techniques: Fractal encoding, Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT). And Following are lossless techniques: Arithmatic Encoding, Run Length Encoding (RLE), and Huffman Encoding. The efficiency of compression process is estimated using Compression Ratio (C.R.) and the quality of reconstructed image which is generated after decompression process is calculated using Peak-Signal-to-Noise Ratio (P.S.N.R.).
References
- Veenadevi. S. V., A. G. Ananth, “Fractal Image Compression of Satellite Imageries,” International Journal of Computer Applications, September 2011.
- Hitashi Gaganpreet Kaur Sugandha Sharma, “Fractal image compression- a review,” International Journal of Advanced Research in Computer Science and Software Engineering, February 2014.
- Xinpeng Zhang, Yanli Ren, Liquan Shen, Zhenxing Qian, and Guorui Feng, “Compressing Encrypted Images With Auxiliary Information,” IEEE Transactions on Multimedia, August 2014.
- Dr. S. S. Pandey, Manu Pratap Singh, Vikas Pandey, “Block Wise Image Compression & Reduced Blocks Artifacts Using Discrete Cosine Transform ,” International Journal of Scientific and Research Publications, March 2015.
- Tim Bruylants, AdrianMunteanu, PeterSchelkens, “Wavelet based volumetric medical image compression,” Elsevier, December 2014.
- Navnidhi Chaturvedi, Dr. S. J. Basha, “Comparison of Digital Image watermarking Methods DWT & DWT-DCT on the Basis of PSNR,” International Journal of Innovative Research in Science, Engineering and Technology, December 2012.
- S. Nigar Sulthana, Mahesh Chandra, “Image Compression with Adaptive Arithmetic Coding,” International Journal of Computer Applications, 2011.
- Rafeeq AL-HASHEMI, Ayman AL-DMOUR, Fares FRAIJ, Ahmed MUSA, “A Grayscale Semi-Lossless Image Compression Technique Using RLE,” Journal of Applied Computer Science & Mathematics, 2011.
- Sharan Kumar, Dr.Jayadevappa, Santosh .D.Bhopale, Radhika R. Naik, “Implementation of Huffman Image Compression And Decompression Algorithm,” International Journal Of Innovative Research In Electrical, Electronics, Instrumentation And Control Engineering, April 2014.
- Gaurav Vijayvargiya, Dr. Sanjay Silakari, Dr.Rajeev Pandey, “A Survey: Various Techniques of Image Compression,” International Journal of Computer Science and Information Security, October 2013.
- Anshuma Patel, Sanjiv Kumar Shriwastava, “Parameterized Comparative Analysis of Various Lossy and Lossless Image Compression Practices,” International Journal of Advanced Research in Computer and Communication Engineering, February 2015.
- Rahul Shukla, Narender Kumar Gupta, “Image Compression through DCT and Huffman Coding Technique,” International Journal of Current Engineering and Technology, May 2015.
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