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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

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Published on: August 30, 2013

Accurate image rotation using hermite expansions.

Wooram Park1, Gregory Leibon, Daniel N Rockmore

  • 1Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. wpark7@jhu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|June 9, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel digital image rotation method using Hermite expansions, achieving superior accuracy compared to existing FFT-based techniques. The approach ensures precise image rotation through efficient coefficient mapping.

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Area of Science:

  • Digital Image Processing
  • Computational Mathematics

Background:

  • Accurate digital image rotation is crucial for various applications.
  • Existing methods like FFT-based rotation can introduce inaccuracies.

Purpose of the Study:

  • To propose an accurate digital image rotation method using Hermite expansions.
  • To develop efficient techniques for mapping Hermite coefficients during rotation.
  • To enable accurate rotation of discrete images.

Main Methods:

  • Utilizing 2-D continuous bandlimited Hermite expansions.
  • Establishing an invertible linear relationship between Hermite coefficients for rotation.
  • Developing two efficient methods for computing coefficient mapping.
  • Proposing a method to connect discrete images with Hermite expansions.

Main Results:

  • The proposed method allows for accurate rotation of discrete images.
  • The Hermite coefficient mapping is efficient and invertible.
  • The new rotation methods demonstrate consistently better accuracy than FFT-based methods.

Conclusions:

  • Hermite expansions provide an accurate framework for digital image rotation.
  • The proposed methods offer a significant improvement in rotation accuracy over FFT-based approaches.
  • This technique is valuable for applications requiring high-fidelity image transformations.