Title :
A low-power video decoder with power, memory, bandwidth and quality scalability
Author :
Chaddha, Navin ; Meng, Teresa H Y
Author_Institution :
Comput. Syst. Lab., Stanford Univ., CA, USA
Abstract :
This paper describes a low-power scalable video decoder for use in portable video applications. The scalable video decoder uses tree structured vector quantization (TSVQ) of perceptually weighted block transforms. The subjective quality of compressed images improves significantly by the use of perceptual distortion measures. The low-complexity, low-power architecture requires only table-lookups to perform video decompression. Inverse transforms are performed as pre-processing steps in the tables. Color conversion from YUV to RGB and color quantization are also performed as pre-processing steps in the tables. The video decoder provides a trade-off between rate-distortion, power and memory size. This allows to trade-off power and memory size for better quality of compressed video and vice-versa. The power consumption of our video decoder is orders of magnitude smaller than other decoders in existing technology. Measured performance shows that the scalable video decoder consumes between 50 to 150 micro-watt with a 1.5 V power supply in 0.8 μ CMOS technology for 160×240 resolution video at 30 frames per second
Keywords :
CMOS digital integrated circuits; decoding; digital signal processing chips; table lookup; vector quantisation; video coding; 0.8 micron; 1.5 V; 50 to 150 muW; CMOS technology; DSP chip; bandwidth scalability; color conversion; color quantization; compressed images; inverse transforms; low-power architecture; low-power video decoder; memory size; perceptual distortion measures; perceptually weighted block transforms; portable video applications; quality scalability; scalable video decoder; table-lookups; tree structured VQ; vector quantization; video decompression; Bandwidth; CMOS technology; Decoding; Distortion measurement; Energy consumption; Image coding; Image converters; Rate-distortion; Vector quantization; Video compression;
Conference_Titel :
VLSI Signal Processing, VIII, 1995. IEEE Signal Processing Society [Workshop on]
Conference_Location :
Sakai
Print_ISBN :
0-7803-2612-1
DOI :
10.1109/VLSISP.1995.527516