Effectiveness of Spectral Similarity Measures to Develop Precise Crop Spectra for Hyperspectral Data Analysis
نویسندگان
چکیده
منابع مشابه
A Geometric View of Similarity Measures in Data Mining
The main objective of data mining is to acquire information from a set of data for prospect applications using a measure. The concerning issue is that one often has to deal with large scale data. Several dimensionality reduction techniques like various feature extraction methods have been developed to resolve the issue. However, the geometric view of the applied measure, as an additional consid...
متن کاملEvaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
متن کاملSpatial/Spectral Analysis of Hyperspectral Image Data
The integration of spatial and spectral responses in hyperspectral image data analysis has been identified as a desirable objective by the remote sensing community. However, most available attempts are based on the consideration of spectral information separately from spatial information, and thus the two types of information are not treated simultaneously. In this paper, we describe our backgr...
متن کاملWavelet-based Analysis of Hyperspectral Data for Detecting Spectral Features
The purpose of feature extraction is to abstract substantial information from the original data input and filtering out redundant information. In this paper we transfer the hyperspectral data from the original-feature space to a scale-space plane by using a wavelet transform to extract significant spectral features. The wavelet transform can focus on localized signal structures with a zooming p...
متن کاملAn information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis
A hyperspectral image can be considered as an image cube where the third dimension is the spectral domain represented by hundreds of spectral wavelengths. As a result, a hyperspectral image pixel is actually a column vector with dimension equal to the number of spectral bands and contains valuable spectral information that can be used to account for pixel variability, similarity, and discrimina...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2014
ISSN: 2194-9050
DOI: 10.5194/isprsannals-ii-8-83-2014