Advanced Learning Techniques for Remote Sensing Image Quality Improvement

Dear Colleagues,

Remote sensing image quality improvement, e.g., image super-resolution, image fusion, and image deblurring, are important foundations and prerequisites for many downstream remote sensing applications. In recent years, although substantial progress has been made in the above directions, there are still some open problems and challenges, such as how recent learning techniques (e.g., deep learning, generative neural networks) reshape and benefit remote sensing image processing, how to effectively evaluate the quality of remote sensing images, and how to deal with the rapidly growing data volume as well as their diverse modalities.

In this Special Issue, we invite you to submit the most recent advancements of this field in terms of methodological contributions as well as innovative applications. The potential topics may include but are not limited to:

• Remote sensing image super-resolution;
• Image registration and pan-sharpening;
• Hyperspectral image denoising;
• Remote sensing image deblurring and dehazing;
• Deep-learning-based remote sensing image processing;
• Multimodal data fusion between hyperspectral imagery with other data sources;
• Cloud detection and removal in remote sensing images;
• Remote sensing image quality assignment;
• Advanced deep learning models, e.g., generative adversarial networks, diffusion probabilistic models, and physics-informed neural networks;
• Advanced learning techniques, e.g., self-supervised learning;
• Real-time processing of remote sensing images;
• Applications of remote sensing image quality improvement in agriculture, marine, meteorology, and other fields

Dr. Zhengxia Zou
Dr. Zhou Zhang
Dr. Haopeng Zhang
Dr. Feng Gao
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 submissions that pass pre-check are 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 250 words) can be sent to the Editorial Office for assessment.

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 2700 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.