3D Information Recovery and 2D Image Processing for Remotely Sensed Optical Images (Third Edition)

Dear Colleagues,

Thank you all for your efforts and support that made the previous volumes of our Special Issue “3D Information Recovery and 2D Image Processing for Remotely Sensed Optical Images” such a success. We have published a number of excellent studies. Due to the overwhelming support for and interest in the previous Special Issues (SIs), we are pleased to announce the release of this third volume to continue tracking the latest improvements in the field of remotely sensed optical images.

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 among 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 three-dimensional information recovery and two-dimensional image processing for remotely sensed optical images. We invite you to participate in this Special Issue by submitting an article. 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
Dr. Wei Yuan
Guest Editors

Manuscript Submission Information

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