Embedded wavelet packet object-based image coding based on context classification and quadtree ordering
In this paper, an object-based embedded image coding algorithm based on context classification and quadtree ordering in wavelet packet domain (OB-CCAQO) is proposed. To match up well with the quadtree-based embedded coder, a new cost function for the best basis selection is adopted in SA-DWPT (shape adaptive discrete wavelet packet transform). The significance probability of wavelet coefficient is estimated by convoluting a 99 9  9 FIR filter matrix kernel with the significance states of neighboring coefficients, and then a context classifier based on LloydMax algorithm is used to categorize the wavelet coefficients with the same or similar significance probability into several contexts. The significance state of wavelet coefficient with respect to a given threshold is encoded using adaptive arithmetic coder based on the classified context. In addition, combined with the structure of the best wavelet packet basis, a complete quadtree representation of wavelet packet coefficients is established to explore the ordering procedure of embedded object-based image coding. Experimental results show that the proposed object-based embedded image coder offers coding performance superior to the popular object-based coders and is also comparable to or better than the state-of-art embedded image coder when applied in the framed-based image coding.
context classification quadtree ordering embedded image coding best wavelet packet basis object-based coding significance probability estimation