In a sign-magnitude representation of binary lattice codevectors, only a few least significant bit-planes are constrained due to the structure of the lattice, while there is no restriction on other more significant bit-planes. Hence, any convenient bit-plane coding method can be used to encode the lattice codevectors, with modification required only for the lattice-defining, least-significant bit-planes. Simple encoding methods for the lattice-defining bit-planes of the D4, RE8, and Barnes-Wall 16-dimensional lattices are described. Simulation results for the encoding of a uniform source show that standard bit-plane coding together with the proposed encoding provide about the same performance as integer lattice vector quantization when the bit-stream is truncated. When the entire bit-stream is fully decoded, the granular gain of the lattice is realized.

A new compression algorithm for fingerprint images is introduced. A modified wavelet packet scheme which uses a fixed decomposition structure, matched to the statistics of fingerprint images, is used. Based on statistical studies of the subbands, different compression techniques are chosen for different subbands. The decision is based on the effect of each subband on reconstructed image, taking into account the characteristics of the Human Visual System (HVS). A noise shaping bit allocation procedure which considers the HVS, is then used to assign the bit rate among subbands. Using Lattice Vector Quantization (LVQ), a new technique for determining the largest radius of the Lattice and its scaling factor is presented. The design is based on obtaining the smallest possible Expected Total Distortion (ETD) measure, using the given bit budget. At low bit rates, for the coefficients with high-frequency content, we propose the Positive-Negative Mean (PNM) algorithm to improve the resolution of the reconstructed image. Furthermore, for the coefficients with low-frequency content, a lossless predictive compression scheme is developed. The proposed algorithm results in a high compression ratio and a high reconstructed image quality with a low computational load compared to other available algorithms.