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  • The frequency domain equalizer is just a complex division per subchannel Channel shortening equalizer is an 20-30 tap FIR filter My focus is on channel shortening

Slides Slides Presentation Transcript

  • Motivation
    • Video Communication over
    • Heterogeneous Networks
      • Diverse client devices
      • Various network connection
      • bandwidths
    • Limitations of Scalable Video
    • Coding Schemes
      • Limited layers supported
      • No video format changes
    • Video Transcoding Provides
    • Dynamic Solutions
      • Channel bandwidth adaptation
      • Video coding format adaptation
  • Challenges in Video Transcoding
    • Improve Efficiency of Video Transcoding
      • Large data volume
      • High computational complexity
    • Optimize Visual Quality for a Given Bit Rate
      • Human vision system (HVS) based video transcoding is desirable
  • Proposed Solutions
    • Exploit Foveation Property of the HVS in Video Transcoding
    • Develop Fast Algorithms for Video Transcoding
      • DCT-domain foveation filtering technique
      • Fast algorithms for DCT-domain inverse motion compensation
        • Local bandwidth constrained DCT-domain inverse motion compensation
        • Look-up-table based DCT-domain inverse motion compensation
  • Foveation
    • The Human Eye Samples Visual Field Non-uniformly
      • The highest sampling resolution is at Fovea
      • The sampling resolution decreases rapidly as away from Fovea
    • Retinal Images are Inherently Non-uniform in Spatial Resolution
    Eccentricity (deg) Cells per degree Eccentricity (left eye)
  • Foveation Modelling
    • Foveated Contrast Threshold [Geisler & Perry 98]
    • Foveated Cut-off Frequency f c
    • Spatial Frequencies Beyond
    • the Cut-off Frequency is
    • Invisible ( Foveated Image )
    • f : Spatial frequency (cyc/degree)
    • e : Retinal eccentricity(degree)
    • a : Spatial frequency decay constant
    • e 2 : Half-resolution eccentricity
    • CT 0 : Minimum contrast threshold
    • CT : Contrast threshold
    Local cut-off frequency (cyc/deg) Pixel position relative to foveation point (unit: pixel) Image size: 512 x 512 Unit of v: image height
  • Foveated Images Foveation point is marked by ‘X’ JPEG-coded Uniform Image (168KB) JPEG-coded Foveated Image (136KB)
  • Foveated Contrast Sensitivity Function (FCSF)
    • Foveated Contrast Sensitivity Function (FCSF)
    • Shape the Compression Distortion According to FCSF
    Image size: 512 x 512 Viewing distance: 3 times the image height Normalized contrast sensitivity of human eye Distance from foveation point (unit: pixel)
  • Video Transcoding Architecture
    • Open-Loop Video Transcoding
      • Simple and fast
      • Error drift
    Transcoding Error Propagation
  • Drift Free Video Transcoders
    • Cascaded Pixel Domain Video Transcoding
      • Low efficiency
      • Long delay
    • Fast Pixel Domain Video Transcoding
      • Save motion estimation, one frame memory and one IDCT operation
    • Fast DCT-Domain Video Transcoding
      • No IDCT-DCT operations; Lower data volume
      • DCT-domain inverse motion compensation is complex (Research topic)
    Fast Pixel Domain Video Transcoder Fast DCT Domain Video Transcoder
  • Foveation Embedded DCT Domain Video Transcoding
  • Foveation Filtering
    • Pixel Domain Foveation Filtering Technique [Lee, 99]
      • High computational complexity
  • DCT-Domain Foveation Filtering
    • DCT-Domain Block Mirror Filtering [Rao, 90]
    • Pros
      • Significantly simplified
      • Combine with inverse quantization
      • Easy to parallelize
    • Cons
      • Blocking artifacts
    Filter Kernel DCT of f h f H. R. Sheikh, S. Liu, B. L. Evans and A. C. Bovik, “ Real-Time Foveation Techniques for H.263 Video Encoding in Software ”, ICASSP 2001.
  • Multipoint Video Conferencing H. R. Sheikh, S. Liu, Z. Wang and A. C. Bovik,“ Foveated Multipoint Videoconferencing at Low Bit Rates ”, ICASSP 2002, accepted.
  • Simulation Results Uniform resolution video at 256 kb/s Foveated video at 256 kb/s Foveation point is at the center of the upper-left quadrant
  • Foveation Point Selection
    • Interactive Methods
      • Mouse, eye tracker
      • Reverse channel is assumed
      • End to end delay is assumed short enough
    • Automatic Methods
      • Fixation points analysis (Very challenging)
      • Application oriented methods
    • DCT-Domain Human Face Detection [Wang & Chang, 97]
      • Skin color region segmentation
      • Face template constraint
      • Spatial Verification