Title :
A fast second-generation encoding algorithm for vector quantization
Author :
Jo, Liza ; Kaimal, M.R.
Author_Institution :
Dept. of Comput. Sci., Kerala Univ., Trivandrum, India
Abstract :
This paper presents a fast encoding algorithm for vector quantization that uses edge information contained in an image in addition to the use of average values of the vectors forming the image. The algorithm makes use of these features to identify the visually significant areas of the image and to save computational time while producing good quality pictures at reasonable computing cost. The simulation results compare well with other existing algorithms of the conventional type.
Keywords :
computational complexity; gradient methods; image coding; image reconstruction; search problems; vector quantisation; EAGNNS; VQ; average values; computational time reduction; edge information; equal average comparable gradient nearest-neighbor search; fast second-generation encoding algorithm; high-quality reconstructed images; image coding; image vectors; lossy data compression; picture quality; simulation results; vector quantization; visually significant areas identification; Acceleration; Computational modeling; Costs; Data compression; Decoding; Encoding; Image coding; Nearest neighbor searches; Signal processing algorithms; Vector quantization;
Journal_Title :
Signal Processing Letters, IEEE
