Combined wavelet with directional filter banks,a non-redundant image transform called as Wavelet-Directional Filter Banks (WDFB) was realized.It fulfilled the anisotropy scaling law and could represent the geometrical features such as edges and texture more sparsely.By taking the advantages of the WDFB,an efficient image compression algorithm based on morphology operator was proposed.The new algorithm used the significant tree to express the correlation of inter-band while utilizing morphological dilation operator to cluster the significant coefficients within sub-band.Experimental results show that the performance of the new algorithm is superior to the wavelet-based algorithms in terms of Peak Signal to Noise Ratio (PSNR),especially for the images including a large portion of texture.For example,for Barbara image of 512×512,at 0.25bpp,PSNR of the new algorithm outperforms that of SPIHT and MRWD by 1.05dB and 0.77dB,respectively.