Context- and HVS-Based Multiwavelet Image Coding Using SPIHT Framework

In this paper, multiwavelets are considered in the context of image compression based on the human vision system (HVS). First, selecting the BSA (4/4)* filters, a twodimensional image is transformed with our proposed algorithm I. Second, we apply HVS coefficients into the subbands of the transformed image. Third, we split the coefficients into two parts: the significance map and residue map. Then a new modified set partitioning in hierarchical trees (SPIHT) algorithm is proposed to encode the significance map. Fourth, algorithm III is presented for coding the residue map. Finally, we adopt context-based adaptive arithmetic coding to encode the bit stream. We also provide some experimental results proving that multiwavelets are worth studying and compare them with those of other multiwavelet and JPEG2000 algorithms.