• Special Issue on Image Optimization in Remote Sensing

    From Don D.@21:1/5 to All on Tue Apr 16 22:28:20 2019
    Journal of Remote Sensing (ISSN 2072-4292). 2017 Impact Factor: 3.406 (Journal Citation Reports)
    Dear Colleagues,

    Remote sensing is defined as the science of analyzing and monitoring physical characteristics of an area with the measurement of its reflected or emitted radiation. Typically, remote sensing information is obtained from airplanes or satellites at a great
    distance from the surface of the earth, enabling regular monitoring of land, ocean, and atmospheric conditions for multiple applications, such as mineralogy, biology, defense, and environmental preservation.

    The data acquired for remote sensing can be represented in the form of images to make its analysis easier. However, such images present interesting characteristics such as a high spectral-spatial-temporal resolution, and multiple channels that provide
    valuable information independently or all together. These facts generate a big amount of information that must be properly and accurately analyzed. Some of the issues related to images from remote sensing applications can be treated as optimization
    problems. Thus, the necessity to design and implement optimization methods that possess a superior performance on the search for optimal solutions for remote sensing applications arises.

    This special issue concerns the implementation and development of optimization techniques able to find the best solutions for processing remote sensing images. In general, in this special issue the latest advances and trends of optimization algorithms
    for remote sensing image processing will be presented, addressing original developments, new applications, and practical solutions to open questions. The aim is to increase the data and knowledge exchange between the optimization and remote sensing
    communities and allow experts from other areas to understand the inherent problematics of remote sensing. Moreover, authors are encouraged to present hybrid methods that might include the use of machine learning approaches.

    The topics for this Special Issue include, but are not limited to, the following:

    3D radar and 3D sonar imaging
    Sonar image processing, data reduction, feature extraction, and image understanding
    Interferometric methods
    Sparse image reconstruction
    Hyperspectral images
    Object extraction and accuracy evaluation in 3D reconstruction
    Satellite images
    Surveillance systems
    Multi-sensor data fusion
    Image segmentation
    Multilevel thresholding
    Clustering
    Metaheuristic Algorithms
    Classical optimization techniques
    Hybrid optimization mechanisms
    Machine learning
    Fuzzy logic approaches
    Neural computing
    Evolutionary computation
    Multi-objective optimization
    Many-objective optimization
    Hyper-heuristics
    Heuristics
    Swarm algorithms
    Feature selection
    Dr. Diego Oliva
    Dr. Salvador Hinojosa
    Dr. Mohamed Abd Elaziz
    Dr. Ahmed A. Ewees
    Guest Editors

    More information: www.mdpi.com/si/22269

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