A Low-Complexity Modeling Approach for Embedded Coding of Wavelet Coefficients

progressive image compression, Laplacian density, run-length coding, rate distortion We present a new low-complexity method for modeling and coding the bitplanes of a wavelet-transformed image in a fully embedded fashion. The scheme uses a simple ordering model for embedding, based on the principle that coefficient bits that are likely to reduce the distortion the most should be described first in the encoded bitstream. The ordering model is tied to a conditioning model in a way that deinterleaves the conditioned subsequences of coefficient bits, making them amenable to coding with a very simple, adaptive elementary Golomb code. The proposed scheme, without relying on zerotrees or arithmetic coding, attains PSNR vs. bit rate performance superior to that of SPIHT, and competitive with its arithmetic coding variant, SPIHT-AC.