Title :
A VLSI architecture for real-time image coding using a vector quantization based algorithm
Author :
Dezhgosha, Kamyar ; Jamali, Mohsin M. ; Kwatra, Subhash C.
Author_Institution :
Dept. of Math. & Comput. Sci., Central State Univ., Wilberforce, OH, USA
fDate :
1/1/1992 12:00:00 AM
Abstract :
Digital image coding using vector quantization (VQ) based techniques provides low-bit rates and high quality coded images, at the expense of intensive computational demands. The computational requirement due to the encoding search process, had hindered application of VQ to real-time high-quality coding of color TV images. Reduction of the encoding search complexity through partitioning of a large codebook into the on-chip memories of a concurrent VLSI chip set is proposed. A real-time vector quantizer architecture for encoding color images is developed. The architecture maps the mean/quantized residual vector quantizer (MQRVQ) (an extension of mean/residual VQ) onto a VLSI/LSI chip set. The MQRVQ contributes to the feasibility of the VLSI architecture through the use of a simple multiplication free distortion measure and reduction of the required memory per code vector. Running at a clock rate of 25 MHz the proposed hardware implementation of this architecture is capable of real-time processing of 480×768 pixels per frame with a refreshing rate of 30 frames/s. The result is a real-time high-quality composite color image coder operating at a fixed rate of 1.12 b per pixel
Keywords :
VLSI; computerised picture processing; data compression; encoding; real-time systems; video signals; 25 MHz; 268 pixels; 480 pixels; MQRVQ; VLSI chip set; clock rate; code vector memory; codebook partitioning; color TV images; composite color image coder; encoding search complexity; hardware implementation; mean/quantized residual vector quantizer; multiplication free distortion measure; real-time image coding; refreshing rate; vector quantization; Color; Computer architecture; Digital images; Distortion measurement; Encoding; Image coding; Large scale integration; TV; Vector quantization; Very large scale integration;
Journal_Title :
Signal Processing, IEEE Transactions on