Spatially Continuous Orientation Adaptive Discrete Packet Wavelet Decomposition for Image Compression

In this paper, we propose an orientation adaptive discrete wavelet transform (DWT) with perfect reconstruction. The proposed transform utilizes the lifting structure to effectively orient the 2D-DWT bases in the direction of local image features. A shifting operator is employed within each lifting step to align spatial geometric features along the vertical or horizontal directions. The proposed oriented transform generates a scalable representation for the image and the orientation information. To approximate the asymptotically optimal rate-distortion performance of a piecewise regular function more closely, we adopt a packet wavelet decomposition. The experimental results obtained by implementing the proposed transform in a JPEG2000 codec illustrate superior compression performance for the oriented transform with more than 2.5 dB improvement for highly oriented natural images. More importantly, even at the same PSNR, the proposed scheme reduces the visual appearance of the Gibbs-like artifacts significantly, considerably improving the visual quality of the reconstructed image.