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Related Experiment Video

Updated: May 11, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Scale-Adaptive High-Resolution Imaging Using a Rotating-Prism-Guided Variable-Boresight Camera.

Zhaojun Deng¹, Anhu Li², Xin Zhao²

¹College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China.

Sensors (Basel, Switzerland)

|October 29, 2025

Summary

This summary is machine-generated.

This study introduces a novel imaging architecture that combines large field-of-view (FOV) imaging with super-resolution (SR) capabilities. The system achieves high-resolution imaging for specific regions of interest while correcting distortions and dispersion.

Keywords:

distortion correction large FOV rotating prisms super-resolution images variable-boresight camera

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Area of Science:

Optical Engineering
Image Processing
Computational Imaging

Background:

Achieving both large field-of-view (FOV) and high-resolution imaging simultaneously presents a significant challenge in imaging technology.
Existing methods often struggle to balance wide-area coverage with the ability to capture fine details.

Purpose of the Study:

To develop a scale-adaptive imaging architecture capable of both large-FOV situational awareness and super-resolution (SR) region-of-interest (ROI) imaging.
To introduce novel methods for distortion and dispersion correction in multi-view imaging.
To enhance image clarity and detail acquisition compared to traditional imaging techniques.

Main Methods:

A rotating-prism-embedded variable-boresight camera architecture was designed to combine multi-view images into a large-FOV image.
A novel distortion correction method utilizing virtual symmetrical prisms with complementary rotation angles was proposed.
A new SR imaging scheme involving a residual removal network and an information enhancement network through multi-view image fusion was developed.
Light reverse tracing was employed for pixel-level compensation to eliminate dispersion.

Main Results:

The proposed architecture successfully demonstrated large-FOV imaging for situational awareness and SR ROI display for detailed acquisition.
Effective correction of image distortion and dispersion was achieved.
The system showed improved image clarity over traditional SR methods and mitigated occlusion to some extent.
The architecture successfully balanced large-scale imaging with high-resolution imaging.

Conclusions:

The developed scale-adaptive imaging architecture effectively integrates large-FOV and high-resolution imaging capabilities.
The novel distortion and dispersion correction methods improve image quality and accuracy.
This approach offers a significant advancement in overcoming the trade-offs between imaging scale and resolution.