Slide 2:
LISS-4 Modis image of kolar dist RAW SATELLITE IMAGE
Aim of the Project Work :
Aim of the Project Work Satellite Image Classification
Input: Satellite image of low Resolution of 1501x1501
Aim: Classification of Land cover and water bodies using unsupervised clustering based algorithms
Additional Aim: Reclassification of classified area
Output: labeled classified image
Performance analysis of classification
Slide 4:
Input
Unclassified
Satellite Image K-Means
Clustering Unsupervised
Classification Mean Shift
Clustering ? Output
Classified satellite Image Re- Classification
Of Classified region Comparison & Performance analysis
Of different Technique
Loop Holes of Existing System :
Loop Holes of Existing System Only primitive methods are used in unsupervised classification of land cover & water bodies
Most of the work using mean shift is on Medical and simpler images.
Various work has not yet proved in a completely satisfactory way the competitiveness of satellite based methods compared with ground measures and aerial surveys
Proposed System :
The Proposed Methodology has been broadly divided
Satellite Image Classification using Clustered based advanced unsupervised clustering method/algorithms like K-means , Mean shift..etc
Mean shift clustering has not been used on satellite image for classification till now, according to literature survey.
Reclassification of classified subsets
Comparison & Performance/Accuracy evaluation of different techniques
Based on evaluation results planning to go for Optimization of classification algorithms using biological inspired technique like PSO (Particle swarm optimization) after first stage of project implementation Proposed System
Slide 7:
Original Satellite Image Classified Satellite Image Sample Input and output
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