Image Classification, Supervised classification #Remote_Sensing #GIS #Geography #Cartography.

Image Classification, Supervised classification #Remote_Sensing #GIS #Geography #Cartography.
Image Classification; 
Supervised classification,
Minimum-distance-to-means,
Parallelepiped,
Gaussian maximum likelihood

#Geographer
#Cartographer
#Globe
#Earth
#Map
#Decision Making

Vineesh V,
Assistant Professor Geography,
Directorate of Collegiate Education,
Government of Kerala, India

[jesnasherin]

Supervised classification is explained in this video. There are 3 types
1.minimum distance to mean classifier
2.parallelepipped classifier
3.Gaussiao maximum likelihood classifier

The minimum distance to mean classifier is simplest mathematically and very efficient in computation. In this procedure the DN value of the training sets are plotted in a scatteromgram.
The parallelpiped classification strategy is also computationally simple and efficient.
Gaussian maximum likelihood classifier is one of the most popular methods of classification in remotesensing, in whicha a pixel with the maximum likelihood is classified in to the corresponding class

[sabarithasivan]

In this video explain supervised classification.
1.Minimum distance to mean classifier
2.pararllellepipped classifier
3.Gaussian maximum likelihood classifier
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image.

[muhammedsuhail]

Supervised classification is explained in this video are there are three types. Minimum distance to main classifier, parallelepiped classifier, Guassiao maximum likelihood classifier.

The minimum distance to main Kasi fire is simplicity mathematically and very efficient in computation .In this procedure the value of the training set your plotted in scattereogram.
The parallelepiped classification strategy is also computationally simple and efficient.

Guassiao maximum likelihood classifier is one of the most popular method of classification in Remote Sensing. in which a pixel with the maximum likelihood is classified into the corresponding class.

[susmithak]

This video explain the supervised classification.

There are three types of supervised classification are listed below :

1.minimum distance to mean classifier
2.parallelepiped classifier
3.Guassian maximum likelihood classifier

Minimum distance to mean classifier method is simple mathematically and very difficult to computations.In this procedure the DN value of the training sets are plotted in a scatterogram.

The second method, parallelepiped classifier is also very simple and efficient.

Guassian method is very popular calculation in remote sensing, in which a pixel wih maximum likelihood is classified in to the corresponding class.
🙂

[geethugs]

Three types of supervised classification are explained here and they are:
1.Minimum distance to Mean Classifier
2.Parallelepiped classifier
3.Guassian Maximum Likelihood classifier

minimum distance to Mean Classifier, this method include simplest mathematical computation.In this DN value of the training sets are plotted in a scattermogram.
2.Parallelepiped classifier
This method is also simple and efficient.In this procedure a rectangular box is fitted for each class is defined by the maximum and minimum values of each bands.
3.Gaussian Maximum Likelihood classifier
It is one of the popular method of classification in remote sensing, in which a pixel with the maximum likelihood is classified into the corresponding class.

[sindhus]

Supervised classification is of 3 types .They are
1.Minimum distance to mean classifier
2.Parallelpipped Classifier
3.Gaussian Maximum Likelihood Classifier
The minimum distance to mean classifier is simplest mathematically and very efficient in computation
In this the DN value of the training sets are plotted in a scatteromgram
The parallelepiped classification strategy is simple and efficient
Gaussian maximum likelihood classification is one of the most popular methods of classification in remote sensing

[joeyalex]

Here's the description of different algorithms of supervised classification. The algorithms are three types and they are : -
1 Minimum distance to mean classiffier
2 Parallelepiped classiffier
3 Guassian maximum likelihood classiffier

1.The minimum distance to mean classiffier is simplest mathematically method. In this procedure the DN value of the training sets are plotted in a scatter diagram
2. This classification strategy is also computationally efficient. In this procedure a rectangular box is fitted for each class is defined by the maximum and minimum values of each bands.
3. The maximum likelihood classiffier is one of the most popular methods of classification in remote sensing, in which a pixel with the maximum likelihood is classified in to the corresponding class.