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Related Experiment Video

Updated: May 30, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Image restoration by matching gradient distributions.

Taeg Sang Cho¹, C Lawrence Zitnick, Neel Joshi

¹WilmerHale, LLP, 60 State Street, Boston, MA 02139, USA. taegsang@gmail.com

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 17, 2011

Summary

This summary is machine-generated.

Iterative Distribution Reweighting (IDR) enhances image deconvolution by preserving textures. This method reconstructs realistic images by matching gradient distributions, outperforming traditional MAP estimators.

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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

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Last Updated: May 30, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Area of Science:

Computer Vision
Image Processing
Computational Imaging

Background:

Image restoration commonly uses MAP estimators, which can remove important image textures.
Sparse gradient priors in MAP estimators lead to piecewise smooth reconstructions, sacrificing visual realism.

Purpose of the Study:

To introduce an alternative deconvolution method, Iterative Distribution Reweighting (IDR).
To improve the visual realism of reconstructed images by preserving textures.

Main Methods:

IDR imposes a global constraint on image gradients, matching a reference distribution.
A reference gradient distribution is estimated per texture segment within the input image.
This approach enables the restoration of rich mid-frequency textures.

Main Results:

The IDR algorithm successfully restores images with rich textures.
Reconstructed images exhibit improved visual realism compared to traditional methods.

Conclusions:

IDR offers a superior alternative to MAP estimators for image deconvolution.
The method effectively enhances visual realism by preserving image textures.