A wavelet is a mathematical function useful in digital signal processing and image compression. The use of wavelets for these purposes is a recent development, although the theory is not new. The principles are similar to those of Fourier analysis, which was first developed in the early part of the 19th century. In signal processing, wavelets make it possible to recover weak signals from noise. This has proven useful especially in the processing of X-ray and magnetic-resonance images in medical applications. Images processed in this way can be "cleaned up" without blurring or muddling the details. In Internet communications, wavelets have been used to compress images to a greater extent than is generally possible with other methods. In some cases, a wavelet-compressed image can be as small as about 25 percent the size of a similar-quality image using the more familiar "JPEG" method. Thus, for example, a photograph that requires 200 KB and takes a minute to download in JPEG format might require only 50 KB and take 15 seconds to download in wavelet-compressed format. Wavelet compression works by analyzing an image and converting it into a set of mathematical expressions that can then be decoded by the receiver. A wavelet-compressed image file is often given a name suffix of "WIF". Either your browser must support these files or it will require a plug-in program to read the fles. Wavelet compression is not yet widely used on the Web. The most common compressed image formats remain the Graphics Interchange Format (GIF), used mainly for drawings, and JPEG, used mainly for photographs