Special Issue "Robust Multispectral/Hyperspectral Image Analysis and Classification"
Deadline for manuscript submissions: 1 December 2019
We observe that satellite imagery, such as a multispectral/hyperspectral image, is a powerful source of information, as it contains different spatial, spectral and temporal resolutions, compared to traditional images. In the past decade, the remote sensing community has introduced intensive works to establish accurate remote sensing image classifiers. However, there are inherent challenges for remote sensing imagery analysis and classification. For example, the quantity of labeled data for remote sensing imagery (e.g., multispectral and hyperspectral image) is limited since it is time-consuming and expensive to obtain a large number of samples with class labels. Also, actual hyperspectral image data inevitably contain considerable noise (Gaussian noise, dead-lines, and other mixed noise) due to the physical limitations of the imaging sensors. In addition, label noise (i.e. mis-labeling of pixels) poses challenges for supervised classification algorithms. Therefore, developing robust image classification and analysis methods that can handle these issues becomes a pressing need for practical applications.
The aim of this Special Issue is to gather cutting-edge works that address the aforementioned challenges in multispectral/hyperspectral image analysis and classification. The main topics include, but not limited to:
- Robust multispectral/hyperspectral image classification algorithms and feature representations under the conditions of
- Noisy data
- Noisy label
- Small sample size
- Data imbalance
- Multispectral/hyperspectral image denoising
- Missing data reconstruction
- Multispectral/hyperspectral data unmixing
- Illumination Enhancement
- Noise robust multispectral/hyperspectral image analysis
- Compressive sensing
- Object/target/anomaly detection
- Feature/corresponding matching
Dr. Junjun Jiang
Dr. Jiayi Ma
Dr. Sidike Paheding
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.
- Multispectral/hyperspectral remote sensing
- Remote sensing image analysis
- Noise robust classification
- Data imbalance
- Computer vision
- Machine learning