3D Information Recovery and 2D Image Processing for Remotely Sensed Optical Images II

Dear Colleagues,

Due to the overwhelming support and interest in the previous Special Issue (SI), we are introducing a second edition on “3D Information Recovery and 2D Image Processing for Remotely Sensed Optical Images”. We would like to thank all the authors and co-authors who contributed to the success of the first edition of this SI.

In the photogrammetry and remote sensing fields, an important and longstanding task is the recovery of the 3D information of scenes, followed by the generation of visually appealing digital orthophoto maps (DOMs) with rich semantic information. Remotely sensed optical images are one of the most widely used data sources. The key technologies of this task include 3D information recovery and 2D image processing. Recently, with the development of deep-learning techniques, many deep-learning-based methods have been proposed in the computer vision field to recover the 3D information of scenes, enhance the image quality, and acquire semantic information. However, almost all of these methods focus on photos taken by smart mobile phones or SLR cameras. Few works have explored these recent advances in remote sensing. Thus, we aim to collect recent research works related to “3D Information Recovery and 2D Image Processing for Remotely Sensed Optical Images”. We invite you to participate in this Special issue by submitting articles. Topics of particular interest include, but are not limited to, the following:

• Feature matching and outlier detection for remote sensing image matching;
• Pose estimation from 2D remote sensing images;
• Dense matching of images acquired by remote sensing for 3D reconstruction;
• Depth estimation of images acquired by remote sensing;
• Texture mapping for 3D models;
• Digital elevation model generation from remotely sensed images;
• Digital orthophoto map generation;
• Image stitching and color correction for remotely sensed images;
• Enhancement, denoising, and super-resolution of images acquired by remote sensing;
• Semantic segmentation and object detection for images obtained by remote sensing.

Dr. Li Li
Prof. Dr. Wei Zhang
Prof. Dr. Jian Yao
Prof. Dr. Andrea Garzelli
Dr. Claudia Zoppetti
Guest Editors

Manuscript Submission Information

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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.

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