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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

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Superresolution of 3-D computational integral imaging based on moving least square method.

Hyein Kim, Sukho Lee, Taekyung Ryu

|November 18, 2014

Summary

This study introduces an edge-directed superresolution method for computational integral imaging reconstruction. The new approach enhances elemental image resolution, overcoming registration errors to achieve high-resolution 3D image reconstruction.

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Area of Science:

Computational Imaging
Image Reconstruction
Superresolution Techniques

Background:

Computational Integral Imaging Reconstruction (CIIR) faces challenges with low-resolution elemental images and microlens alignment errors.
These issues hinder accurate registration, limiting the application of superresolution to CIIR.
Existing methods struggle with abrupt brightness changes and registration inaccuracies.

Purpose of the Study:

To propose an Edge Directive Moving Least Square (ED-MLS) based superresolution method for CIIR.
To address the limitations of registration errors and enhance elemental image resolution.
To introduce a data acquisition framework for superresolution in CIIR.

Main Methods:

Utilizing the properties of Moving Least Square (MLS) reconstruction.
Incorporating edge directionality into the MLS to handle abrupt brightness changes.
Developing a framework for data collection tailored to superresolution in CIIR.

Main Results:

The proposed ED-MLS method effectively enhances the resolution of elemental images.
The method demonstrates reduced sensitivity to registration errors.
High-resolution 3D images are successfully reconstructed using the proposed technique.

Conclusions:

The ED-MLS based superresolution method significantly improves CIIR.
The approach overcomes key challenges in integral imaging registration and resolution enhancement.
The proposed framework facilitates effective superresolution for 3D image reconstruction in CIIR.