Special Issue "Image Processing and Analysis: Trends in Registration, Data Fusion, 3D Reconstruction, and Change Detection II"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 31 December 2022.

Special Issue Editors

Dr. Riccardo Roncella
E-Mail Website
Guest Editor
Department of Engineering and Architecture, Università degli Studi di Parma, Parco Area delle Scienze, 181/a, 43124 Parma, PR, Italy
Interests: image matching; image orientation; satellite/airborne/UAV photogrammetry; 3D reconstruction; monitoring; laser scanning; vision metrology
Special Issues and Collections in MDPI journals
Dr. Mattia Previtali
E-Mail Website
Guest Editor
Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Giuseppe Ponzio, 31, 20133 Milano, MI, Italy
Interests: image analysis; image matching; multiview reconstruction; laser scanning; point cloud classification; monitoring
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Satellite, aerial, UAV, and terrestrial imaging techniques are constantly evolving in terms of data volumes, quality, and variety. Earth observation programs, both public and private, are making available a growing amount of multitemporal data, often publicly accessible, at an increased spatial resolution and with a high revisit time. At the opposite end of the platform scale, UAVs, due to their higher flexibility, represent a new paradigm for acquiring high-resolution information with high frequencies. Similarly, consumer-grade 360° cameras and hyperspectral sensors are more and more widespread in different terrestrial platforms and applications.

Remotely sensed data can provide the basis for timely and efficient analysis in several fields, such as land usage and environmental monitoring, cultural heritage, archaeology, precision farming, human activity monitoring, and other engaging research and practical fields of interest. Availability, the increasing need for fast and reliable responses, and the increment of the number of active (but often unskilled) users all pose new relevant challenges in research fields connected to data registration, data fusion, 3D reconstruction, and change detection. In this context, automated and reliable techniques are needed to process and extract information from such a large amount of data.

This Special Issue is the second edition on these subjects (1st edition available at https://0-www-mdpi-com.brum.beds.ac.uk/journal/remotesensing/special_issues/rs_image_trends) and aims at presenting the latest advances of innovative image analysis and image processing techniques and their contribution in a wide range of application fields, in an attempt to foresee where they will lead the discipline and practice in the coming years. As far as process automation is concerned, it is of utmost importance to invest in an appropriate understanding of the algorithmic implementation of the different techniques and identify their maturity as well as possible applications where their use might leverage their full potential. For this reason, aspects of interest include (i) accuracy: the agreement between the reference (check) and measured data (e.g., accuracy of check point in image orientation or accuracy of testing set in data classification); (ii) completeness: the amount of information obtained from different methodologies and their space/time distribution; (iii) reliability: algorithm consistency, intended as stability to noise, and algorithm robustness, intended as estimation of the measurements’ reliability level and capability to identify gross errors; and (iv) processing speed: the algorithm computational load.

The scope includes but is not limited to the following:

  • Image registration and multisource data integration or fusion methods;
  • Deep learning methods for data classification and pattern recognition;
  • Automation in thematic map production (e.g., spatial and temporal pattern analysis, change detection, and definition of specific change metrics);
  • Cross-calibration of sensors and cross-validation of data/models;
  • Orientation in a seamless way of images acquired with different platforms;
  • Object extraction and accuracy evaluation in 3D reconstruction;
  • Low-cost 360° and fisheye consumer-grade camera calibration, orientation, and 3D reconstruction;
  • Direct georeferencing of images acquired by different platforms.

Dr. Riccardo Roncella
Dr. Mattia Previtali
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Image registration
  • Change detection
  • 3D reconstruction
  • Deep learning
  • Hyperspectral
  • Image matching
  • Data/sensor fusion
  • Object-based image analysis
  • Pattern recognition

Published Papers (1 paper)

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Technical Note
A Practical 3D Reconstruction Method for Weak Texture Scenes
Remote Sens. 2021, 13(16), 3103; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13163103 - 06 Aug 2021
Viewed by 380
Abstract
In recent years, there has been a growing demand for 3D reconstructions of tunnel pits, underground pipe networks, and building interiors. For such scenarios, weak textures, repeated textures, or even no textures are common. To reconstruct these scenes, we propose covering the lighting [...] Read more.
In recent years, there has been a growing demand for 3D reconstructions of tunnel pits, underground pipe networks, and building interiors. For such scenarios, weak textures, repeated textures, or even no textures are common. To reconstruct these scenes, we propose covering the lighting sources with films of spark patterns to “add” textures to the scenes. We use a calibrated camera to take pictures from multiple views and then utilize structure from motion (SFM) and multi-view stereo (MVS) algorithms to carry out a high-precision 3D reconstruction. To improve the effectiveness of our reconstruction, we combine deep learning algorithms with traditional methods to extract and match feature points. Our experiments have verified the feasibility and efficiency of the proposed method. Full article
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