Land cover classification using reformed fuzzy C-means
نویسندگان
چکیده
منابع مشابه
Sar Image Classification Using Fuzzy C-means
Image Classification is the evolution of separating or grouping an image into different parts. The good act of recognition algorithms based on the quality of classified image. The good feat of recognition algorithms based on the quality of classified image. An important problem in SAR image application is accurate classification. Image segmentation is the mainly practical loom among virtually a...
متن کاملHyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach
Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval...
متن کاملClassification of Land Use and Land Cover in the Brazilian Amazon using Fuzzy Multilayer Perceptrons
Here the authors propose the use of Fuzzy Multilayer Perceptrons for classification of land use and land cover patterns in the Brazilian Amazon, using time series of vegetation index, taken from NASA’s MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. In addition to the traditional Multilayer Perceptron (MLP), three fuzzy implementations were investigated. These methods were applied...
متن کاملUrban Land Cover Classification Using Hyperspectral Data
Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...
متن کاملAudio signal segmentation and classification using fuzzy c-means clustering
This paper proposes an audio signal segmentation and classification method using fuzzy c-means clustering. Recently, high performance of the audio signal segmentation and classification is required for audio-visual indexing because of the popular use of the Internet, higher bandwidth access to the network, widespread of digital recording and storage; and several methods have been proposed. They...
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: Sadhana
سال: 2011
ISSN: 0256-2499,0973-7677
DOI: 10.1007/s12046-011-0018-4