In this paper, a technique to reduce the overhead of Vector Quantization (V
Q) coding is developed here. Our method exploits the inter-index correlatio
n property to reduce the overhead to transmit encoded indices. Discrete Cos
ine Transform (DCT) is the tool to decorrelate the above correlation to get
further bit rate reduction. As we know, the codewords in the codebook that
generated from conventional LEG algorithm do not have any specified orders
. Hence, the indices for selected codewords to represent respective adjacen
t blocks are random distributions. However, due to the homogeneous property
existing among adjacent regions in original image, we re-arrange the codeb
ook according to our predefined weighting criterion to enable the selected
neighboring indices capable of indicating the homogeneous feature as well.
Then, DCT is used to compress those VQ encoded indices. Because of the homo
geneous characteristics existing among the selected adjacent indices after
codebook permutation, DCT can achieve better compression efficiency. Howeve
r, as we know, DCT introduces distortion by the quantization procedure, whi
ch yield error-decoded indices. Therefore, we utilize an index residue comp
ensation method to make up that error decoded indices which have high compl
exity deviation to reduce those unpleasant visual effects caused by distort
ed indices. Statistics illustrators and table are addressed to demonstrate
the efficient performance of proposed method. Experiments are carried out t
o Lena and other natural gray images to demonstrate our claims. Simulation
results show that our method saves more than 50% bit rate to some images wh
ile preserving the same reconstructed image qualities as standard VQ coding
scheme.