Representing a image using a Haar-Wavelet Transformation for human parts detection

The computer is becoming more and more powerful day by day. As a result, the use of digital images is increasing rapidly. The image is actually a kind of redundant data. By using data compression techniques, it is possible to remove some of the redundant information contained in images. Irrelevancy reduction omits parts of the signal that is not noticed by the signal receiver, namely the Human Visual System (HVS). Wavelet can be effectively used for this purpose. Wavelet-based coding provides substantial improvements in picture quality at higher compression ratios. Wavelet based image compression is encouraging feature of wavelet transform is its symmetric nature that is both the forward and the inverse transform has the same complexity, building fast compression and decompression routines. A image compression method using Haar wavelets as the basis functions quality measurement of the compressed images. This paper review the Haar Wavelet Transformation is a simple form of compression involved in averaging and differencing terms, storing detail coefficients, eliminating data, and reconstructing the matrix.