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Special Issue "Remote Sensing Applications of Image Denoising and Restoration"
Deadline for manuscript submissions: 30 June 2020.
Interests: signal and image processing; machine learning; hyperspectral image analysis; multisensor data fusion; remote sensing
Interests: remote sensing data analysis; hyperspectral image analysis; machine learning; spectral unmixing
Special Issues and Collections in MDPI journals
Interests: machine (deep) learning; hyperspectral image analysis; multisensor data fusion
Special Issues and Collections in MDPI journals
Special Issue in ISPRS International Journal of Geo-Information: Data Mining and Feature Extraction from Satellite Images and Point Cloud Data
Special Issue in Remote Sensing: Advances in Earth Observations Analytics: Leveraging Radar and Optical Together
Special Issue in Remote Sensing: Advanced Multisensor Image Analysis Techniques for Land-Cover Mapping
Special Issue in Remote Sensing: Deep Learning and Data Mining for Hyperspectral Imagery
Special Issue in Remote Sensing: Image Processing and Spatial Neighbourhoods for Remote Sensing Data Analysis
Recent advances in remote sensing technologies have presented a broad range of applications related to Earth observation and monitoring. Remotely sensed data are often degraded by different noise sources and artifacts that appear differently in different data acquisition technologies and sensors. The received radiance in optical remote sensing data is often degraded by mixed noise. Push-broom scanning induces striping noise in spectral imaging technologies. Light detection and ranging (LiDAR) data are degraded by impulse noises, and synthetic aperture radar (SAR) suffers from speckle noises. On the other hand, noise reduction and data restoration can improve the signal-to-noise ratio of acquired data and consequently affect remote sensing applications. However, the complexity and variety of remote sensing imaging technologies make the denoising and restoration of different data sources, from ground measurements to aerial and space measurements, very challenging. This Special Issue aims to address these problems by providing a variety of contributions focused on the application of image denoising and restoration in remote sensing data analysis. Additionally, this Special Issue promotes the use of image denoising and restoration as a preprocessing step for further remote sensing data processing. Therefore, the Special Issue’s contributions include (but are not limited to) remote sensing applications of the following topics:
- Mixed noise reduction for hyperspectral images;
- Despeckling for synthetic aperture radars;
- Destriping for optical imagery;
- Image inpainting;
- Drone-borne sensor restoration and image denoising;
- Advanced image processing for restoration and denoising;
- Advanced machine learning and deep learning techniques for image restoration and denoising;
- Artifacts removal from remote sensing data, including ground-, drone (UAV)-, aerial-, and space-based measurements;
- Image demosaicking for remote sensing data;
- The application of image denoising and restoration for classification, land-cover mapping, super-resolution and sharpening, unmixing, target detection, change detection, multitemporal remote sensing analysis, and data fusion.
Dr. Behnood Rasti
Prof. Dr. Paul Scheunders
Dr. Pedram Ghamisi
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 1800 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.
- sparse noise
- mixed noise
- artifact removal
- remote sensing