A still image encoder based on adaptive resolution vector quantization employing needless calculation elimination architecture

We have developed an advanced vector quantization (VQ) encoding hardware for still image encoding systems. By utilizing needless calculation elimination method, computational cost of VQ encoding is reduced to 40% or less, while maintaining the accuracy of full-search VQ. We have successfully implemented the advanced encoding method and Adaptive resolution VQ (AR-VQ), which realizes compression ratio over 1/200 while maintaining image quality, into a still image encoding processor. The processor can compress still image of 1600 x 2400 pixels within one second, which is 60 times faster than software implementation on current PCs.

[1]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[2]  K. Kotani,et al.  A still image encoder based on adaptive resolution vector quantization realizing compression ratio over 1/200 featuring needless calculation elimination architecture , 2002, 2002 Symposium on VLSI Circuits. Digest of Technical Papers (Cat. No.02CH37302).

[3]  T. Morimoto,et al.  A fully-parallel vector quantization processor for real-time motion picture compression , 1997, 1997 IEEE International Solids-State Circuits Conference. Digest of Technical Papers.

[4]  K. Kotani,et al.  A parallel vector-quantization processor eliminating redundant calculations for real-time motion picture compression , 2000, IEEE Journal of Solid-State Circuits.