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Related Experiment Video

Updated: May 16, 2026

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
07:11

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation

Published on: December 8, 2023

Correspondence map-aided neighbor embedding for image intra prediction.

Safa Cherigui1, Christine Guillemot, Dominique Thoreau

  • 1Research and Innovation at Technicolor, Cesson Sévigné 35576, France. safa.cherigui@technicolor.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|November 30, 2012
PubMed
Summary

This study introduces map-aided neighbor embedding (MANE) for improved image prediction. These novel methods enhance coding efficiency by better handling non-homogenous textures, outperforming existing techniques.

Related Experiment Videos

Last Updated: May 16, 2026

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
07:11

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation

Published on: December 8, 2023

Area of Science:

  • Digital image processing
  • Video compression algorithms
  • Machine learning for computer vision

Background:

  • Neighbor embedding (NE) approximates image blocks using K nearest neighbors.
  • Existing NE methods struggle with non-homogenous textures due to poor template correlation.
  • H.264 Intra prediction modes offer a benchmark for image prediction efficiency.

Purpose of the Study:

  • To develop advanced image prediction methods overcoming limitations of traditional NE techniques.
  • To introduce map-aided neighbor embedding (MANE) and its optimized variant (oMANE).
  • To significantly improve rate-distortion performance in image and video coding.

Main Methods:

  • Utilizing K-NN search in a two-step process aided by a block correspondence map (MANE).
  • Implementing an optimized variant (oMANE) with alternative K-NN search strategies.
  • Comparing performance against H.264 Intra prediction modes.

Main Results:

  • MANE and oMANE demonstrate significant rate-distortion improvements.
  • Achieved up to 44.75% rate saving at low bit rates compared to H.264 Intra modes.
  • Enhanced prediction accuracy, especially in challenging non-homogenous texture areas.

Conclusions:

  • MANE and oMANE represent a substantial advancement in image prediction techniques.
  • These methods offer superior performance for video compression, particularly at lower bitrates.
  • The block correspondence map effectively addresses limitations of prior NE approaches.