Image compression using complex wavelet transform

Discrete wavelet transform (DWT) became a powerful method for signal processing in the last decade. One of the most important applications of this tool is compression, for the bi-dimensional signals JPEG 2000 being an example. Although the new standard offers better results than the old one, new innovating ideas can improve even the JPEG 2000. One idea is to use complex wavelet transforms, transforms that offers more directions, instead of classical DWT. This paper comes to show the superiority of complex wavelet transforms in image compression, testing a new transform developed by N.G. Mngsbury. For this, the Embedded Zero-Tree Wavelet (EZW) algorithm proposed by Shapiro was used to compress images at some different bit rates.