Validation And Implementation Of Spiht For Image Compression(Set Partitioning In Hierarchical Trees )

Validation And Implementation Of Spiht For Image Compression(Set Partitioning In Hierarchical Trees )

Abstract:

Embedded zerotree wavelet coding introduced by J.M.Shapiro[1] is a very effective and computationally simple technique for image compression and is the basic of all image compression techniques.SPIHT is a new and different image compression technique whose implementation is based on set partitioning in hierarchical trees which provides better performance than previously reported EZW and suppress the performance of the original EZW and offers fast execution. In addition, coding and decoding procedures are extremely fast ad they can be made even faster, with only small loss in performance.

 Need of compression: In many different fields, digitized images are replacing conventional analog images as photographs or X-rays .The volume of data required to describe such images greatly slow transmission and make storage prohibitively costly.  A fundamental goal of data compression is to reduce the bit rate for transmission or storage while maintaining acceptable image quality. Compression can be achieved by transforming the data by using a suitable transform  (mainly wavelet transform ) [2]  and then encoding this transformed data.

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