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PSNR Comparison of Lifting Wavelet Decomposed Modified SPIHT Coded Image with Normal SPIHT Coding
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 102 - Number 15 |
| Year of Publication: 2014 |
| Authors: Ashish Nautiyal, Isha Tyagi, Mukesh Pathela |
10.5120/17891-8888
|
Ashish Nautiyal, Isha Tyagi, Mukesh Pathela . PSNR Comparison of Lifting Wavelet Decomposed Modified SPIHT Coded Image with Normal SPIHT Coding. International Journal of Computer Applications. 102, 15 ( September 2014), 16-21. DOI=10.5120/17891-8888
Abstract
Today's world is the era of communication i. e. sending some information from one point to another. And images are one of the commonly used multimedia, because of the application in almost every field of engineering i. e. biomedical, astronomical, geological etc. To make communication fast and efficient with respect to images, compression is needed in each and every field. Idea behind the work is to reduce the size of image at transmitter end and after sending it to the receiver, regenerate it again to its original form. But to attain a measurable amount of compression, there are always some losses (compromise on resolution) at receiver end. The measure of efficiency of compression coding depends upon the balance between resolution and compression ratio of images. So aim of every coding scheme is to make a good trade-off between resolution and compression ratio so that we can achieve a fast communication with a good regenerated image at the receiver end. In this work, compression is based on wavelet transform. Wavelet is an important tool to covert spatial domain representation into frequency domain which is not based on a fundamental frequency of sine or cosine waveform of infinite period of time but finite numbers of short waves of different frequencies which give the best result for high frequency components as well as for low frequency (long time period) components too. After transforming the image, lower and higher energy parts can be easily differentiated and quantization can be applied to truncate the unnecessary lower energy parts where higher energy is kept preserve. For coding of transformed image, a Set Partitioning in Hierarchical Tree (SPIHT) coding algorithm is used. After the transformation, SPIHT coding scheme basically code high energy components first and progressively transmits the coded bits to make an increasingly refined copy of the original image. A modified SPIHT coding is presented in the work for progressive transmission.
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