6533b826fe1ef96bd1283ab1
RESEARCH PRODUCT
Adaptive motion estimation and video vector quantization based on spatiotemporal non-linearities of human perception
J.m. ArtigasJesús MaloFrancesc J. FerriJesús V. Albertsubject
Signal processingAdaptive algorithmComputer sciencebusiness.industryTrellis quantizationQuantization (signal processing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVector quantizationIterative reconstructionOptical flow estimationMotion estimationComputer Science::MultimediaHuman visual system modelDiscrete cosine transformComputer visionArtificial intelligencebusinessQuantization (image processing)description
The two main tasks of a video coding system are motion estimation and vector quantization of the signal. In this work a new splitting criterion to control the adaptive decomposition for the non-uniform optical flow estimation is exposed. Also, a novel bit allocation procedure is proposed for the quantization of the DCT transform of the video signal. These new approaches are founded on a perception model that reproduce the relative importance given by the human visual system to any location in the spatial frequency, temporal frequency and amplitude domain of the DCT transform. The experiments show that the proposed procedures behave better than their equivalent (fixed-block-size motion estimation and fixed-step-size quantization of the spatial DCT) used by MPEG-2.
year | journal | country | edition | language |
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1997-01-01 |