Libao ZHANG^1,2* and Bingchang QIU¹

¹College of Information Science and Technology, Beijing Normal University, Beijing 100875, China
²State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

(Received May 8, 2013; Accepted July 24, 2013)

The traditional lifting wavelet transform cannot effectively reconstruct the nonhorizontal and nonvertical high-frequency information of an image. In this paper, we present a new image compression method based on adaptive directional prediction discrete wavelet transform (ADP-DWT). We first design a directional prediction model to obtain the optimal transform direction of the lifting wavelet. Then, we execute the directional lifting transform along the optimal transform direction. The edge and texture energy can be reduced in the nonhorizontal and nonvertical directions of the high-frequency sub-bands. Finally, the wavelet coefficients are coded with the set partitioning in hierarchical trees (SPIHT) algorithm. The new method holds the advantages of both adaptive directional lifting (ADL) and direction-adaptive discrete wavelet transform (DA-DWT), and the computational complexity is far lower than that in these methods. For the images containing regular and fine textures or edges, the coding preformance of ADP-DWT is better than that of ADL and DA-DWT.

Key words: image compression, discrete wavelet transform, lifting scheme, adaptive directional prediction, SPIHT

^*E-mail address: libaozhang@163.com