摘要或動機

Video compression is indispensable to web streaming and memory storage.Most video\r
compression technology has difficulty to achieve high quality video at lower bit\r
rates.Apparently,limited transmission bandwidth and network resources often degrade\r
video signals.Thus the goal of my research was to enhance video degrade video\r
signals.Thus the goal of my research was to enhance video compression performance and\r
to improve visual quality.It is hypothesized that the reduction in neighboring pixels\r
coding,and humans perceptual mechanisms(psychovisual)redundancy could produce a\r
low-complexity geometry streams for animated visual objects.A set of algorithms is\r
developed to parse bidirectional interpolation pixels into their characteristic cells,which\r
vary in spectral energy and wavelength.The bits contained in these cells are vectorized and\r
transformed recursively to identify lower correlations among vector arrarys for blocks\r
filtering.DCT function calculates energy ratios between high spatial frequency and low\r
spatial frequency,to devote most of the highest spatial frequency bits with the calculated\r
energy ratios.A variable quantization method is used to measure the sensitivity of colors\r
and its intensity ratios to restore any missing high spatial frequency pixels.presnted in\r
mathematical intrinsic.This approach leads to the ability to compress video data that\r
normally require a large amount of memory to store and high bandwidth to\r
transmit,Results form the enhanced video compression experiment have attained\r
0.1bpp(256kbps,25fps)without noticeable effects comparable to the video compression\r
technique that achieved 0.5bpp(1.5Mbps,25fps)in use today.