Remote Sensing Image Restoration and Reconstruction

Dear Colleagues,

In real cases, remote sensing images usually suffer from noises (Gaussian noise, stripe noise, impulse noise, spectral noise, speckle noise, temporal noise, mixed noise, etc.); data missing (thick/thin cloud, shadow, sensor malfunction etc.); and spatial resolution degradation due to equipment limitations, working conditions, limited radiance energy, and generally narrow band width. These phenomena severely degrade the quality of remote sensing images and limit the performance of the subsequent processing, e.g., classification, unmixing, and target detection. Therefore, it is a critical preprocessing step to improve the quality of remote sensing images. Remote sensing image restoration and reconstructing provides solutions to deal with above degradation problems.

This Special Issue concerns the restoration and reconstructing methods and applications for processing remote sensing images. In general, in this Special Issue, the latest advances and trends of restoration and reconstructing algorithms and applications for remote sensing image processing will be presented, addressing novel thoughts and practical solutions to above questions. The aim is to increase the data usability and quality of remote sensing images. Moreover, authors are encouraged to present hybrid methods that might include the use of machine learning approaches. Topics of interest include but are not limited to the following:

• Remote sensing image denoising;
• Remote sensing image fusion;
• Remote sensing image super resolution;
• Remote sensing image missing data reconstruction;
• Remote sensing image radiation correction;
• Remote sensing image geometric correction;
• Remote sensing image restoration.

Prof. Liangpei Zhang
Prof. Huanfeng Shen
Prof. Qiangqiang Yuan
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 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 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.