scholarly journals Survey of Multispectral Image Fusion Techniques in Remote Sensing Applications

10.5772/10548 ◽  
2011 ◽  
Author(s):  
Dong Jiang ◽  
Dafang Zhuang ◽  
Yaohuan Huang ◽  
Jinying Fu
Keyword(s):  
Remote Sensing ◽  
Image Fusion ◽  
Multispectral Image ◽  
Sensing Applications ◽  
Remote Sensing Applications

RNN-based multispectral satellite image processing for remote sensing applications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Venkata Dasu Marri ◽  
Veera Narayana Reddy P. ◽  
Chandra Mohan Reddy S.
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Deep Learning ◽  
Image Classification ◽  
Satellite Image ◽  
Multispectral Image ◽  
Content Type ◽  
Colliding Bodies Optimization ◽  
Sensing Applications ◽  
Remote Sensing Applications

Purpose Image classification is a fundamental form of digital image processing in which pixels are labeled into one of the object classes present in the image. Multispectral image classification is a challenging task due to complexities associated with the images captured by satellites. Accurate image classification is highly essential in remote sensing applications. However, existing machine learning and deep learning–based classification methods could not provide desired accuracy. The purpose of this paper is to classify the objects in the satellite image with greater accuracy. Design/methodology/approach This paper proposes a deep learning-based automated method for classifying multispectral images. The central issue of this work is that data sets collected from public databases are first divided into a number of patches and their features are extracted. The features extracted from patches are then concatenated before a classification method is used to classify the objects in the image. Findings The performance of proposed modified velocity-based colliding bodies optimization method is compared with existing methods in terms of type-1 measures such as sensitivity, specificity, accuracy, net present value, F1 Score and Matthews correlation coefficient and type 2 measures such as false discovery rate and false positive rate. The statistical results obtained from the proposed method show better performance than existing methods. Originality/value In this work, multispectral image classification accuracy is improved with an optimization algorithm called modified velocity-based colliding bodies optimization.

scholarly journals Image fusion techniques for remote sensing applications

2002 ◽  
Vol 3 (1) ◽  
pp. 3-15 ◽  
Author(s):  
G. Simone ◽  
A. Farina ◽  
F.C. Morabito ◽  
S.B. Serpico ◽  
L. Bruzzone
Keyword(s):  
Remote Sensing ◽  
Image Fusion ◽  
Sensing Applications ◽  
Remote Sensing Applications

scholarly journals Image Fusion for Remote Sensing Applications

10.5772/22899 ◽  
2011 ◽  
Author(s):  
Leila Fonseca ◽  
Laercio Namikawa ◽  
Emiliano Castejon ◽  
Lino Carvalho ◽  
Carolina Pinho ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Fusion ◽  
Sensing Applications ◽  
Remote Sensing Applications
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