Improving vector quantization of satellite images through the application of bi-orthogonal wavelets

Abstract

In image coding applications, vector quantization fvQ) h a p widely been accepted as an e€fective compression mettted for digital images. However, its--effectiveness depends greatly on the matching of the VQ elements with the image data values.Prior to #e VQ process, orthogonal transforms such as a DCT or FFT are often used convert an image in the spatial domain to transform fficients in the frequency domain. In this paper, instead of orthogonal transform coeffieknts, bi-orthogonal wavelet Wers are used to transform a sateltttehage to the scalefrequency domain.The wavelet coefficients are vector quantized and their statistical feacres are analyzed in details such as c w t a t i o n a l complexity and perfermance efficiency. Some examples will be shown in the presentation to illustrate the advantage of uskg bi-orthogonal wavelets e the matching of VQ elements to