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Review
14 February 2024

Computational imaging technology (CIT), with its many variations, addresses the limitations of industrial design. CIT can effectively overcome the bottlenecks in physical information acquisition, model development, and resolution by being tightly coupled with mathematical calculations and signal processing in information acquisition, transmission, and interpretation. Qualitative improvements are achieved in the dimensions, scale, and resolution of the information. Therefore, in this review, the concepts and meaning of CIT are summarized before establishing a real CIT system. The basic common problems and relevant challenging technologies are analyzed, particularly the non-linear imaging model. The five typical imaging requirements–distance, resolution, applicability, field of view, and system size–are detailed. The corresponding key issues of super-large-aperture imaging systems, imaging beyond the diffraction limit, bionic optics, interpretation of light field information, computational optical system design, and computational detectors are also discussed. This review provides a global perspective for researchers to promote technological developments and applications.

3,790 views
3 citations
Original Research
31 January 2024
A low-cost close-range photogrammetric surface scanner
Panagiotis Koutlemanis
4 more and 
Ioanna Demeridou

Introduction: A low-cost, close-range photogrammetric surface scanner is proposed, made from Computer Numerical Control (CNC) components and an off-the-shelf, consumer-grade macro camera.

Methods: To achieve micrometer resolution in reconstruction, accurate and photorealistic surface digitization, and retain low manufacturing cost, an image acquisition approach and a reconstruction method are proposed. The image acquisition approach uses the CNC to systematically move the camera and acquire images in a grid tessellation and at multiple distances from the target surface. A relatively large number of images is required to cover the scanned surface. The reconstruction method tracks keypoint features to robustify correspondence matching and uses far-range images to anchor the accumulation of errors across a large number of images utilized.

Results and discussion: Qualitative and quantitative evaluation demonstrate the efficacy and accuracy of this approach.

2,455 views
2 citations
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Frontiers in Imaging

Advancements in SAR Imaging for Disaster Management and Environmental Monitoring
Edited by Pasquale Imperatore, Gianfranco Fornaro, Hanwen Yu, Ronny Hänsch
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20 May 2025
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