A New, Fast and Efficient Wavelet Based Image Compression Technique using JPEG2000 with EBCOT versus SPIHT
Dr. P. Sumitra, Professor, Vasavi Vidya Trust Group of Institutions (Vysya College Campus), Affiliated to Anna University, Chennai (Tamil Nadu), India.
Manuscript received on 21 May 2013 | Revised Manuscript received on 28 May 2013 | Manuscript published on 30 May 2013 | PP: 80-84 | Volume-2 Issue-2, May 2013 | Retrieval Number: B0604052213/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A wavelet is a function like a small wave and a ripple of baseline. The Wavelet Transform (WT) is a technique for analyzing signals. It was developed as an alternative to the Short Time Fourier Transform (STFT) to overcome the problems related to its frequency and time resolution properties. Wavelet can be used to represent data as diverse as heart beats and television signals, in a way that reduces redundancy within the signal. Therefore it can be used for image compression. This paper focuses important features of wavelet transform in compression of still images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression. The techniques used are Set Partitioning In Hierarchical Trees (SPIHT) and Embedded Block Coding Optimal Truncation Code (EBCOT). These techniques are more efficient and provide a better quality in the image. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity. The above techniques have been successfully used in many applications. The techniques are compared by using the performance parameters PSNR. Images obtained with those techniques yield very good results.
Keywords: EBCOT, JPEG2000, SPIHT, DWT, VQ, SQ.
Scope of the Article: Data Mining Methods, Techniques, and Tools