Wavelet Domain Image Interpolation via Statistical Estimation

Abstract

We propose a new wavelet domain image interpolation scheme based on statistical signal estimation. A linear composite MMSE estimator is constructed to synthesize the detailed wavelet coefficients as well as to minimize the mean squared error for high-resolution signal recovery. Based on a discrete time edge model we use low-resolution information to characterize local intensity changes and perform resolution enhancement accordingly. A linear MMSE estimator follows to minimize the estimation error. Local image statistics are involved in determining the spatially adaptive optimal estimator. With knowledge of edge behavior and local signal statistics the composite estimation is able to enhance important edges and to maintain the intensity consistency along edges. Strong improvement in both the visual quality and thel PSNRs of the interpolated images has been achieved by the proposed estimation scheme.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA414065

Entities

People

  • Michael T. Orchard
  • Stuart C. Schwartz
  • Ying Zhu

Organizations

  • Princeton University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Composite Materials
  • Data Science
  • Electrical Engineering
  • Estimators
  • High Resolution
  • Image Processing
  • Information Science
  • Intensity
  • Interpolation
  • Low Resolution
  • Optimal Estimators
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Estimation
  • Statistics

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Statistical inference.