Sensitivity analysis of low-complexity vector quantizers for focal-plane image compression
作者： J.G.R.C. Gomes , S.K. Mitra
DOI: 10.1109/ISCAS.2004.1329913
关键词:
摘要: Most high-performance block-coding systems for image compression, such as JPEG, have been designed software or dedicated digital hardware implementations where the data are already assumed to be available in format. In modern CMOS photosensors, smart-pixel technologies allowed realization of basic signal processing tasks at pixel level, analog format before analog-to-digital (A/D) conversion. The elimination A/D converters and implementation directly over blocks pixels sensors can attractive both terms area savings power consumption. design block encoders, under strong constraints that derive from converter removal, has investigated this paper. We present a comparison three rate, distortion complexity, numerical simulation analysis their sensitivity errors. conclusion is linear-transform coding vector quantizers outperform full-search warping hyperbolic-tangent neural networks, performance, complexity robustness, imaging sensor implementation.
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