Title :
The optimization of vector quantizers by minimizing variance
Author_Institution :
Dept. of Electr. Eng., Ohio Northern Univ., Ada, OH, USA
Abstract :
This paper presents the results of the optimization of a vector quantizer designed to quantize the coefficients from the transform coding of black and white images. Eight images were coded using 4×4 blocks of pixels which were in turn transformed using the discrete cosine transform. Three separate methods of optimization were investigated including the Linde-Buzo-Gray (1984) method, a simulated annealing method and a third method which minimizes the variance associated with each codebook value of the vector quantizer. Results indicate that the minimum variance method optimizes the codebook nearly as well as the simulated annealing method, but with much less processing time
Keywords :
discrete cosine transforms; image coding; minimisation; simulated annealing; vector quantisation; DCT; Linde-Buzo-Gray method; black and white images; codebook; coefficients quantisation; discrete cosine transform; minimum variance method; optimization; pixels; processing time; simulated annealing method; transform coding; vector quantizers; Design optimization; Discrete Fourier transforms; Discrete cosine transforms; Discrete transforms; Frequency; Image coding; Optimization methods; Pixel; Simulated annealing; Transform coding;
Conference_Titel :
System Theory, 1994., Proceedings of the 26th Southeastern Symposium on
Conference_Location :
Athens, OH
Print_ISBN :
0-8186-5320-5
DOI :
10.1109/SSST.1994.287810