An approach based on self-organizing map and fuzzy membership for decomposition of mixed pixels in hyperspectral imagery
نویسندگان
چکیده
منابع مشابه
Hyperspectral image classification using an unsupervised neuro-fuzzy system
An unsupervised neuro-fuzzy system, Gaussian fuzzy self-organizing map (GFSOM), is proposed for hyperspectral image classification. This algorithm operates by integrating an unsupervised neural network with a Gaussian function-based fuzzy system. We also explore the potential for hyperspectral image analysis of three other artificial intelligence (AI)-based unsupervised techniques popular for m...
متن کاملCategory Decomposition Method Based on Matched Filter for Un-Mixing of Mixed Pixels Acquired with Spaceborne Based Hyperspectral Radiometers
Category decomposition method based on matched filter for un-mixing of mixed pixels: mixels which are acquired with spaceborne based hyperspectral radiometers is proposed. Through simulation studies with simulated mixed pixels which are created with spectral reflectance data derived from USGS spectral library as well as actual airborne based hyperspectral radiometer imagery data, it is found th...
متن کاملCrop Land Change Monitoring Based on Deep Learning Algorithm Using Multi-temporal Hyperspectral Images
Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...
متن کاملSeparation Between Anomalous Targets and Background Based on the Decomposition of Reduced Dimension Hyperspectral Image
The application of anomaly detection has been given a special place among the different processings of hyperspectral images. Nowadays, many of the methods only use background information to detect between anomaly pixels and background. Due to noise and the presence of anomaly pixels in the background, the assumption of the specific statistical distribution of the background, as well as the co...
متن کاملMonthly runoff forecasting by means of artificial neural networks (ANNs)
Over the last decade or so, artificial neural networks (ANNs) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. However, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. For this reason, this study aims at de...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 31 شماره
صفحات -
تاریخ انتشار 2010