Fast orientation prediction-based discrete wavelet transform for remote sensing image compression

Abstract

In this letter, a fast orientation prediction-based discrete wavelet transform (DWT) is introduced for high-spatial-resolution remote sensing image compression. The proposed fast orientation prediction-based approach is designed to improve coding performance and reduce computational complexity of the previous adaptive directional lifting method. The main contribution of the proposed approach consists of three parts: a new orientation map is designed to achieve a better transform coding performance; an orientation prediction model is presented to fast obtain the optimal transform orientation; the new fast orientation prediction-based DWT is introduced. Experimental results show that the proposed fast orientation prediction-based high-spatial-resolution remote sensing image coding technique outperforms the traditional lifting wavelet and the method based on adaptive directional lifting in coding performance, and the computational complexity of the proposed transform is far lower than that of adaptive directional lifting method.

Funding

This work was sponsored by National Natural Science Foundation of China [61071103], and Fundamental Research Funds for the Central Universities [2012LYB50].