Pyramidal lattice vector quantization(PLVQ) has drawn extensive attention by its promising property recently. The coding method based on zerotree (ZR) coding [1] has made a great coup during the last few years. Based on the traits of dyadic wavelet decomposition of signal and that of the distribution of wavelet image coefficients

PLVQ and ZR are conjoined by making use of D-4 lattice. Firstly

Pyramidal lattice vector quantization is adopted to quantize wavelet image coefficients. Nonzero lattice vectors and zero lattice vectors are formed. Secondly

nonzero lattice vectors are dealt with by adopting complex entropy coding. Finally

in order to fix on the position of nonzero lattice vector effectively

that is

to deal with zero lattice vectors effectively

the concept of significant map is introduced into. The significant map is scanned two times from down to up and from up to down. Based on this and the probability distribution of zerotree roots

zero lattice vectors are disposed by adopting improved zerotree coding. Experimental results demonstrate that the proposed algorithm performs better than traditional entropy coding based on runlength.