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High resolution image formation from low resolution frames using Delaunay triangulation.

S Lertrattanapanich1, N K Bose

  • 1Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA 16802, USA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
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This study introduces a new algorithm for creating high-resolution (HR) images from low-resolution (LR) frames using Delaunay triangulation and polynomial approximation. The method allows for real-time image processing and quality enhancement as more frames become available.

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Geometry

Background:

  • Generating high-resolution (HR) images from low-resolution (LR) sequences is crucial for various applications.
  • Existing super-resolution techniques often struggle with computational complexity and real-time processing.

Purpose of the Study:

  • To develop an efficient algorithm for constructing high-resolution images from multiple low-resolution frames.
  • To enable real-time image sequence processing with adaptive quality enhancement.

Main Methods:

  • Utilizes spatial tessellation and Delaunay triangulation to approximate image patches with bivariate polynomials.
  • Incorporates a site-insertion algorithm for iterative refinement of the high-resolution image.
  • Applies post-filtering for final image quality optimization.

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Main Results:

  • The algorithm successfully constructs high-resolution images with high quality from low-resolution frames.
  • The method demonstrates suitability for real-time processing due to efficient Delaunay triangulation and local updates.
  • Iterative updates allow for continuous quality improvement as more data becomes available.

Conclusions:

  • The proposed algorithm offers an effective and efficient solution for super-resolution image reconstruction.
  • Its real-time processing capability and adaptive refinement make it valuable for dynamic image sequences.