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Updated: Jun 3, 2026
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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
Published on: February 12, 2014
Principle of superposition by direction images
1Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249-0669, USA. amgrigoryan@utsa.edu
Summary
This study introduces a novel image decomposition method using tensor and paired representations. This technique enables unique image decomposition into direction images, aiding in image reconstruction from projection data.
Area of Science:
- Digital Image Processing
- Signal Processing
- Mathematical Imaging
Background:
- Traditional image analysis often relies on spatial or frequency domain methods.
- Image decomposition is crucial for various applications, including image reconstruction.
- Existing methods may have limitations in handling specific image properties or data types.
Purpose of the Study:
- To present a novel image decomposition technique based on tensor and paired representations.
- To define and utilize 'splitting-signals' for image analysis.
- To establish a framework for image reconstruction from projection data using the proposed method.
Main Methods:
- Decomposition of a 2-D image (N×N) using tensor and paired representations.
- Defining the image in the frequency-and-time domain as a set of 1-D signals (splitting-signals).
- Calculating splitting-signals as sums of image pixels along parallel lines to derive direction images.
Main Results:
- A unique decomposition of images into direction images is described.
- Formulas for inverse tensor and paired transforms are provided.
- The method facilitates image reconstruction from projections using derived splitting-signals or direction images.
Conclusions:
- The tensor and paired representations offer a powerful framework for image decomposition.
- The derived formulas enable efficient image reconstruction from projection data.
- The number of projections required is determined by the tensor representation of the image.
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