[DMANET] [cfp] Special Issue on Image Optimization in Remote Sensing, MDPI

DEADLINE 31 March 2020.

Special Issue on Image Optimization in Remote Sensing

Journal of Remote Sensing (ISSN 2072-4292). 2017 Impact Factor: 4.118
(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

--
Dr. Diego Oliva
diegoliva.com <http://www,diegoliva.com>

**********************************************************
*
* Contributions to be spread via DMANET are submitted to
*
* DMANET@zpr.uni-koeln.de
*
* Replies to a message carried on DMANET should NOT be
* addressed to DMANET but to the original sender. The
* original sender, however, is invited to prepare an
* update of the replies received and to communicate it
* via DMANET.
*
* DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET)
* http://www.zaik.uni-koeln.de/AFS/publications/dmanet/
*
**********************************************************