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Articles 1 - 3 of 3
Full-Text Articles in Engineering
A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
Electrical and Computer Engineering Faculty Publications
This paper presents a novel VQ structure which provides very good quality encoding for video sequences and exploits the computational savings gained from a fast-search algorithm. It uses an adaptive-search, variable-length encoding method which allows for very fast matching of a wide range of transmission rates. Both the encoding quality and the computational benefits from the fast-search algorithm are presented. Simulations show that full-search tree residual VQ (FTRVQ) can provide up to 3 dB improvement over a similar RVQ encoder on video sequences.
Design Of An Fpga-Based High-Speed Filter-Decimator For The Gifts Imaging Interferometer, Scott E. Budge, Charles R. O'Brien
Design Of An Fpga-Based High-Speed Filter-Decimator For The Gifts Imaging Interferometer, Scott E. Budge, Charles R. O'Brien
Electrical and Computer Engineering Faculty Publications
This paper presents the design of an FPGA-based frame filter-decimator for the geostationary imaging Fourier transform spectrometer (GIFTS). The decimator reduces samples from two 128/spl times/128 sample imaging arrays from 1638.4 fps to 102.4 complex fps for the long wave IR (LWIR) band and from 1638.4 fps to 204.8 complex fps for the medium wave IR (MWIR) band. The design uses a novel parallel pipeline architecture to handle the bandpass sampling and decimation of the 16 k array samples which arrive a frame-at-a-time. The design is challenging because of significant speed, size, weight and power restrictions for satellite implementation.
Very Fast Tree-Structured Vector Quantization, Todd K. Moon, Christian B. Peel, Scott E. Budge
Very Fast Tree-Structured Vector Quantization, Todd K. Moon, Christian B. Peel, Scott E. Budge
Electrical and Computer Engineering Faculty Publications
Very fast tree-structured vector quantization employs scalar quantization decisions at each level, but chooses the dimension on which to quantize based on the coordinate direction of maximum variance. Because the quantization is scalar, searches are no more complex than scalar quantization - providing significant improvement in complexity over full-searched or even tree-structured vector quantization - but the method preserves the shape and memory advantages of conventional vector quantization. However, the space filling advantage of VQ is forfeited, since each Voronoi cell is a rectangular cuboid.