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Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sens...
Creating high-performance means to manage massive hyperspectral data (HSD) arrays is an actual challenge when it is implemented to deal with disparate information resources. Aiming to solve this probl...
Investigation of civil engineering materials includes a wide range of applications that requires three-dimensional (3D) information. Complex structures shapes and formations within heterogeneous art...
The high-dimensional feature vectors of hyper spectral data often impose a high computational cost as well as the risk of "over fitting" when classification is performed. Therefore it is necessary to ...
A new dynamical dimensional reduction model (HDRM) for hyperspectral images is proposed based on clone selection algorithm which is inspired from nature immune system in this paper. In existing dimens...
Assessing the quality of a hyperspectral image is a difficult task. However, this assessment is required at different levels of the instrument design: evaluation of the signal to noise ratio necessary...
By reason of recent advances in airborne and ground-base hyperspectral imaging technology, many applications have been developed. One of the most important hyperspectral images applications involves a...
Effective and understanding exploration of hyperspectral remote sensing data necessitates the development of sophisticated schemes that represent images. Such schemes ideally preserve and recognize si...
Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better...
In most remotely sensed images, because of earth surface topography and sun zenith and azimuth angles, some of features place in shadow and consequently will not be classified and related to the app...
The improved spectral resolution of modern hyperspectral sensors provides effective means for discrimination of subtly different classes and objects. However, in order to obtain statistically reliabl...
The ability of hyperspectral image (HSI) data to provide estimates of soil electrical conductivity (ECa) and soil fertility levels without requiring extensive field data collection was investigated....
Spectral mixing is inherent in any finite-resolution digital imagery of a heterogeneous surface, so that mixed pixels are inevitably created when multispectral images are scanned. Solving the spectra...
In this paper, the quality metrics evaluation on hyperspectral images has been presented using k-means clustering and segmentation. After classification the assessment of similarity between original i...
This paper combine two conventional feature extraction methods (NWFE&NPE) in a novel framework and present a new semi-supervised feature extraction method called Adjusted Semi supervised Discriminant ...

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