31Jul 2017

COMPARATIVE ANALYSIS OF IMAGE COMPRESSION USING WAVELET TRANSFORM.

  • M.Tech. Scholar Jaipur, Department of Electronics and Communication Engineering.
  • Professor, Department of Electronics and Communication Engineering, Arya College of Engineering & IT, Kukas, Jaipur.
  • Professor, Department of Electronics and Communication Engineering, Arya College, Kukas, Jaipur.
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Recent advances in networking and digital media technologies have created a large number of networked multimedia applications. Uncompressed multimedia (graphics, audio and video) data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density, processor speeds, and digital communication system performance, demand for data storage capacity and data-transmission bandwidth continues to outstrip the capabilities of available technologies. The recent growth of data intensive multimedia-based web applications has not only sustained the need for more efficient ways to encode signals and images but have made compression of such signals central to storage and communication technology. Data compression which can be lossy or lossless is required to decrease the storage requirement and better data transfer rate. One of the best image compression techniques is using wavelet transform. It is comparatively new and has many advantages over others. Wavelet transform uses a large variety of wavelets for decomposition of images. The state of the art coding techniques like EZW, SPIHT (set partitioning in hierarchical trees) and EBCOT(embedded block coding with optimized truncation)use the wavelet transform as basic and common step for their own further technical advantages. The wavelet transform results therefore have the importance which is dependent on the type of wavelet used. In our project, we have used HAAR wavelets to perform the transform of different test image and the results have been discussed and analyzed. The analysis has been carried out in terms of PSNR (peak signal to noise ratio) obtained and time taken for decomposition and reconstruction.

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[Dhanashri Kansal, Hemant Kumar Gupta and Rahul Srivastava. (2017); COMPARATIVE ANALYSIS OF IMAGE COMPRESSION USING WAVELET TRANSFORM. Int. J. of Adv. Res. 5 (Jul). 2625-2629] (ISSN 2320-5407). www.journalijar.com

Dhanashri Kansal
1M.Tech. Scholar Jaipur, Department of Electronics and Communication Engineering

DOI:

Article DOI: 10.21474/IJAR01/5006      
DOI URL: https://dx.doi.org/10.21474/IJAR01/5006

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