In this paper

a new approach for optimization design of biorthogonal wavelet filter in image compression is presented. In the process of image encoding

we start with the principle of choosing wavelet bases

make the widely used Antonini's 9/7 wavelet basis the baseline solution

exploit the image compression method of the set partitioning in hierarchical tree(SPIHT)

find the optimization filter coefficients of a biortherogonal filter bank that gives the image compression the best performance. We use Lena as the standard train image

make the compression rate as parameter

apply the genetic method and find the optimization of biorthogonal wavelet filter banks that maximizes the PSNR. It is an optimization problem. In train and test

the results are that the image compression performance is better to use the new optimization biorthogonal filter banks than the Antonini's 9/7 biorthogonal filter banks.