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Related Experiment Videos

Transform coefficient histogram-based image enhancement algorithms using contrast entropy.

Sos S Agaian1, Blair Silver, Karen A Panetta

  • 1College of Engineering, University of Texas at San Antonio, San Antonio, TX 78249-0669, USA. sagaian@utsa.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|March 16, 2007
PubMed
Summary
This summary is machine-generated.

This study introduces novel image enhancement techniques using logarithmic transform coefficient histograms. These methods improve image quality efficiently by mimicking human visual perception.

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Human visual system-based image enhancement and logarithmic contrast measure.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2008

Area of Science:

  • Digital Image Processing
  • Computer Vision
  • Human Visual Perception

Background:

  • Histograms are widely used in image processing.
  • Transform coefficient histograms offer unexplored potential for image enhancement.

Purpose of the Study:

  • To explore transform coefficient histograms for image enhancement.
  • To propose and evaluate new image enhancement algorithms based on logarithmic transform domain histograms.

Main Methods:

  • Developed three enhancement methods: logarithmic transform histogram matching, shifting, and shaping with Gaussian distributions.
  • Utilized properties of logarithmic transform domain histograms and histogram equalization.
  • Defined a human visual system-based quantitative measurement for contrast improvement.

Main Results:

  • Presented experimental results demonstrating the performance of the proposed algorithms.
  • Showcased the effectiveness of logarithmic transform domain histogram manipulation for image enhancement.
  • Validated the quantitative measurement for selecting optimal enhancement parameters.

Conclusions:

  • The proposed logarithmic transform domain histogram methods offer efficient and effective image enhancement.
  • The integration of human visual system principles enhances image contrast quantitatively.
  • This work opens new avenues for applying histogram techniques in the transform domain.