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Perceptual feedback in multigrid motion estimation using an improved DCT quantization.

J Malo1, J Gutierrez, I Epifanio

  • 1Dept. d'Opt., Valencia Univ. Jesus.Malo@uv.es

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 8, 2008
PubMed
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This study introduces a novel video coder that uses human visual system (HVS) models for better motion compensation. The new method improves video quality by balancing motion estimation and redundancy reduction for more meaningful results.

Area of Science:

  • Computer Vision
  • Video Coding
  • Human Visual System Perception

Background:

  • Current video coding methods often lack perceptually optimized distortion control.
  • Adaptive motion estimation and redundancy removal are key to efficient video compression.

Purpose of the Study:

  • To develop a multigrid motion compensation video coder incorporating human visual system (HVS) contrast discrimination models.
  • To enhance video compression by restricting perceptual distortion and optimizing motion estimation.

Main Methods:

  • A novel prediction error encoding procedure was developed, limiting perceptual distortion per transform coefficient.
  • Subjective redundancy removal incorporated amplitude nonlinearities and temporal aspects of human perception.
  • A perceptually weighted control for adaptive motion estimation was derived from HVS models.

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Main Results:

  • Perceptual feedback in motion estimation balanced estimation effort with redundancy removal.
  • The feedback strategy induced scale-dependent refinement, leading to more robust motion estimation.
  • Subjective improvements were demonstrated compared to H.263 and MPEG-like schemes.

Conclusions:

  • The proposed HVS-based video coder offers perceptually superior performance.
  • The method provides more meaningful motion estimation, potentially aiding higher-level sequence interpretation.
  • Integrating human perception models enhances video compression efficiency and subjective quality.