Hiii....i am in need of matlab code for image compression using spiht algorithm...can u provide tat code..

This WWW page presents the powerful wavelet-based image compression method called Set Partitioning in Hierarchical Trees (SPIHT). This award-winning method has received worldwide acclaim and attention since its introduction via this web site in 1995. Thousands of people, researchers and practioners alike, have now tested and used SPIHT. It has become the benchmark state-of-the-art algorithm for image compression.

The SPIHT method is not a simple extension of traditional methods for image compression, and represents an important advance in the field. The method deserves special attention because it provides the following:

good image quality, high PSNR, especially for color images;
it is optimized for progressive image transmission;
produces a fully embedded coded file;
simple quantization algorithm;
fast coding/decoding (nearly symmetric);
has wide applications, completely adaptive;
can be used for lossless compression.
can code to exact bit rate or distortion;
efficient combination with error protection.
Each of these properties is discussed below. Note that different compression methods were developed specifically to achieve at least one of those objectives. What makes SPIHT really outstanding is that it yields all those qualities simultaneously. So, if in the future you find one method that claims to be superior to SPIHT in one evaluation parameter (like PSNR), remember to see who wins in the remaining criteria.



Image Quality

Extensive research has shown that the images obtained with wavelet-based methods yield very good visual quality. At first it was shown that even simple coding methods produced good results when combined with wavelets. SPIHT belongs to the next generation of wavelet encoders, employing more sophisticated coding. In fact, SPIHT exploits the properties of the wavelet-transformed images to increase its efficiency.

Many researchers now believe that encoders that use wavelets are superior to those that use DCT or fractals. We will not discuss the matter of taste in the evaluation of low quality images, but we do want to say that SPIHT wins in the test of finding the minimum rate required to obtain a reproduction indistinguishable from the original. The SPIHT advantage is even more pronounced in encoding color images, because the bits are allocated automatically for local optimality among the color components, unlike other algorithms that encode the color components separately based on global statistics of the individual components. You will be amazed to see that visually lossless color compression is obtained with some images at compression ratios from 100-200:1.

If, after what we said, you are still not certain that you should believe us (because in the past you heard claims like that and then were deeply disappointed), we understand you point of view.

There are three things you can do to convince yourself

Take a look at some of our images.
Visit John Kominek's Waterloo BragZone, where you will find an independent comparative evaluation of different image compression methods. Several methods were tested, and SPIHT proved to be outstanding. (Note: our programs are called SAPA & SAPB there.) In the Waterloo BragZone you will find plenty of images, graphs, etc. If you note that some method or program is missing, consider that maybe their authors refused to have it compared!
Use our demo programs to test SPIHT in your own images.
While using the programs please recall that:

SPIHT is a coding method. So, if you find a reconstruction artifact remember that it may be caused by the particular wavelet transform used by the encoder, and not by the coding process. The choice of the best transform for different image types is still open.
The presently available versions of SPIHT were not designed for synthetic graphical images, so read below what we have to say about them.
The lossy compression programs have a "smoothing factor" that is different from the smoothing factor used by other programs (see FAQ).