Image classification consists of image processing algorithms for grouping cells of similar characteristics together. Satellite image classification is essential to extract the information and identify the different components such as water dense region, roads, vegetation etc. from the classified image. In this paper, an attempt is made to locate and identify the different regions of interest using classification algorithms such as K means and Fuzzy-C Means. Comparison is done for both the algorithms in terms of computational time and memory requirements. Also, the algorithms are applied for the input image by considering different values of K and its discussion is presented in the paper. The algorithms are then applied for the given image w...
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
In this thesis, a detailed review is performed on some existed unsupervised classification algorithm...
ABSTRACT: Image clustering is a process of dividing an image into different meaningful parts base on...
Land cover classification is an essential input to environmental and land use planning.Clustering is...
Image clustering is a critical and essential component of image analysis to several fields and could...
In the context of land-cover classification with multispectral satellite data several unsupervised c...
This paper presents a new approach for color based image segmentation by applying Fuzzy c-means algo...
This thesis describes an investigation into automatic recognition of satellite imagery from the LAND...
Nowadays, integrated land management is generally governed by the principles of sustainability. Land...
The aim of this paper is to classify satellite imagery using moment's features extraction with K-Mea...
Clustering is an unsupervised classification method widely used for classification of remote sensing...
Abstract- Classification of satellite images plays a vital role in remote sensing applications. Nume...
Satellite image segmentation is an important topic in many domains. This paper introduces a novel se...
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The un...
ABSTRACT: A real scene observed from a satellite image contains a variety of features, textures and ...
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
In this thesis, a detailed review is performed on some existed unsupervised classification algorithm...
ABSTRACT: Image clustering is a process of dividing an image into different meaningful parts base on...
Land cover classification is an essential input to environmental and land use planning.Clustering is...
Image clustering is a critical and essential component of image analysis to several fields and could...
In the context of land-cover classification with multispectral satellite data several unsupervised c...
This paper presents a new approach for color based image segmentation by applying Fuzzy c-means algo...
This thesis describes an investigation into automatic recognition of satellite imagery from the LAND...
Nowadays, integrated land management is generally governed by the principles of sustainability. Land...
The aim of this paper is to classify satellite imagery using moment's features extraction with K-Mea...
Clustering is an unsupervised classification method widely used for classification of remote sensing...
Abstract- Classification of satellite images plays a vital role in remote sensing applications. Nume...
Satellite image segmentation is an important topic in many domains. This paper introduces a novel se...
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The un...
ABSTRACT: A real scene observed from a satellite image contains a variety of features, textures and ...
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
In this thesis, a detailed review is performed on some existed unsupervised classification algorithm...
ABSTRACT: Image clustering is a process of dividing an image into different meaningful parts base on...