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Noise estimation and filtering using block-based singular value decomposition.

K Konstantinides1, B Natarajan, G S Yovanof

  • 1Hewlett-Packard Co., Palo Alto, CA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces a novel nonlinear filtering algorithm for image and video preprocessing. The new method enhances image quality and compression performance while preserving edge details.

Area of Science:

  • Image processing
  • Computer vision
  • Signal processing

Background:

  • Spatial filtering is crucial for enhancing image and video quality.
  • Improving compressibility without sacrificing quality is a key challenge in image and video processing.

Purpose of the Study:

  • To develop a block-based, nonlinear filtering algorithm for image and video preprocessing.
  • To evaluate the algorithm's effectiveness in improving image quality and compression performance.

Main Methods:

  • Singular value decomposition (SVD) based filtering.
  • Compression-based filtering techniques.
  • Block-based nonlinear filtering approach.

Main Results:

  • The proposed filter effectively preserves edge details in image and video sequences.

Related Experiment Videos

  • Significant improvements in compression performance were observed.
  • Enhanced image quality was achieved through spatial filtering.

    • Conclusions:

    • The developed nonlinear filtering algorithm offers a promising solution for image and video preprocessing.
    • The method balances image quality enhancement with improved compressibility.
    • This approach is beneficial for applications requiring high-quality, compressed visual data.