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Abstract
The field of image and video compression has gone through rapid growth during the past thirty years, leading to various coding standards. The main goal of continuous efforts on image/video coding standardization is to achieve low bit rate for data storage and transmission, while maintaining acceptable distortion.In present every multimedia device is based on battery operated system. As we know power consumption is crucial part for those device. So there is need of fast and efficient algorithm and hardware unit for those multimedia devices.as we already know compression unit is the most important part for any multimedia device. So, in this paper, various developmental stages of image and video compression standards are reviewed, including JPEG and JPEG 2000 image standards, MPEG-1, MPEG-2, MPEG-4, H.261, H.263, H.264/MPEG-4 AVC, and the latest international video standard HEVC as well as Chinese video coding standard AVS.here we also did the complete comparative discussion between different compression unit in term of time complexity and quality
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How to Cite
Shandilya, S., & Singh, K. (2015). A Review Paper on Image Compression Unit Using DCT. International Journal of Emerging Trends in Science and Technology, 2(05). Retrieved from https://igmpublication.org/ijetst.in/index.php/ijetst/article/view/683
References
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2. Jongsun Park; Jung-Hwan Choi; Roy, K., "Dynamic Bit-Width Adaptation in DCT: An Approach to Trade O_ Image Quality and Computation Energy,"Very Large Scale Integration (VLSI) Systems, IEEE Transactions on , May 2010.
3. Gupta, V.; Mohapatra, D.; Raghunathan, A.; Roy, K., "Low-Power Digital Signal Processing Using Approximate Adders," Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on, Jan. 13.
4. K. Lee, M. Kim, N. Dutt, and N. Venkatasubramanian, "Error-exploiting video encoder to extend energy/qostradeo_s for mobile embedded systems," vol. 271, pp. 2334, 2008.
5. Zhou Wang; Bovik, A.C.; Sheikh, H.R.; Simoncelli, E.P., "Image quality assessment: from error visibility to structural similarity," Image Processing,IEEE Transactions on , vol.13, no.4, pp.600,612, April 2004 doi:10.1109/TIP.2003.819861
6. Wei Zheng; Yanchang Liu, "Research in a fast DCT algorithm based on JPEG," Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on , 16-18 April 2011
7. Yuebing Jiang; Pattichis, M., "Dynamically recon_gurable DCT architectures based on bitrate, power, and image quality considerations," Image Processing (ICIP), 2012 19th IEEE International Conference on ,Sept. 30 2012-Oct. 3 2012
8. Jongsun Park; Jung-Hwan Choi; Roy, K., "Dynamic Bit-Width Adaptation in DCT: An Approach to Trade O_ Image Quality and Computation Energy,"Very Large Scale Integration (VLSI) Systems, IEEE Transactions on , May 2010
9. Emre, Y.; Chakrabarti, C., "Data-path and memory error compensation technique for low power JPEG implementation," Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE Int. Conference on , 22-27 May 11
10. http://www.cdnconnect.com/image-optimization-compression-reducing-file-sizes
11. Strang, Gilbert. "The discrete cosine transform." SIAM review 41.1 (1999): 135-147.