Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Different techniques of Finite-State Vector Quantization, in the image
coding framework are investigated in this paper. Introduced in this paper are
two FSVQ designs, conventional vector quantization and side-match vector
quantization. Convention Vector Quantization divides an image into
K-dimensional blocks where each vector x is mapped to its corresponding code vector
from a codebook of size N. It exploits the correlation between adjacent pixels
within a block of pixels. The encoder of a vector quantizer uses the previously
encoded blocks to make a selection from a family of codebooks. Although vector
quantization provides an acceptable visual quality of the compressed image, it
does it at the cost of increased bit rate. The Side Match Vector Quantization
reduces the bit rate required for storage and transmission of the image and
provides a good visual quality image. SMVQ requires creating its own state
codebook for each block for encoding as well as decoding. SMVQ takes advantage
of the spatial contiguity of pixel vectors by exploiting the correlations of
the nearest neighboring blocks. They try to minimize the granular noise that
causes the annoying effect of visible pixel block boundaries in conventional
VQ. Since the conventional method for the generation of state codebook for SMVQ
is time consuming, the method of rapid generation of state codebook proposes a
fast method for codebook generation.
In this paper, different
image compression techniques of vector quantization, side-match vector
quantization and rapid generation of state codebook method will be implemented
to evaluate the best possible method. Although each technique is an improvement
over the other, the proposed method for rapid generation of state codebook is
faster than the others and without any loss of perpetual visual quality. The
Linde-Buzo-Gray algorithm, also known as LBG algorithm, is used for the
generation of codebooks.
Country : Ireland
IRJIET, Volume 4, Issue 7, July 2020 pp. 1-8