Discrete wavelet transform-based simple range classification strategies for fractal image coding

An efficient fractal method based on discrete wavelet transfer is proposed in this paper. Before encoding, images with one-level wavelet transform are first partitioned into four subbands, which classify the range blocks as four types. An accelerated fractal coding method called variance sorting (VS) scheme with high reconstructed quality is addressed for the low-frequency components. Hereafter, the low-frequency part rebuilt performs one-level wavelet decomposition once again. The first-level high-frequency subbands excluding the diagonal directions are predicted according to the next coarser frequency scale in the same directions. Simulation experimental results compared with other classification algorithms demonstrate that the proposed method can obtain high compression ratio and reduce the encoding time without significant loss in the reconstructed image quality.