SPECTRAL IMAGE PROCESSING USING PYTHON

Teacher

MANOJ KUMAR PADHI

Category

Skill Courses

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Course Name : SPECTRAL IMAGE PROCESSING USING PYTHON

Code(Credit) : CUTM3111(0-2-2)

Course Objectives

• To study the spectral python tool for processing Hyperspectral images.
• To study the concept of Hyperspectral remote sensing.
• To know the basics, importance, and methods of Spectral remote sensing.
• To study machine learning technology for processing hyperspectral images.

Learning Outcomes

• To understand the structure of spectral data including band associations, shape and size of a hyperspectral images
• To develop software skills in programs used for map production in the modern cartographic workflow.
• To develop skills for deploy machine learning technology for processing multispectral and hyperspectral images.

Course Syllabus

Module 1

Practice:
1. Downloading multispectral satellite data from USGS/Bhuban etc
2. Installation of Python (Integrated Development and Learning Environment, Colab Notebook, Python 3.5 or above versions)

Module 2

Practice:
1. Reading multispectral data in python interface.
2. Reading hyperspectral data in pyhton interface.

Module 3

Practice:
1. installing dependencies library and visualization tools in Python such as Rasterio, shapely, GDIL, Spy, Matplotlib, Fiona, etc.
2. Check the shape and size of the image.

Module 4

Practice:
1. Importing Training dataset l.e Ground truth image of one band.
2. Display selected/filtred bands of Hyperspectral image.
3. Superimpose Ground truth image on Hyperspectral image.

Module 5

Practice:
1. Unsupervised classification of Hyperspectral image.

Module 6

Practice:
1. Supervised Classification of Hyperspectral image.

Module 7

Practice:
1. PCA for Dimensionality reduction of Hyperspecral image.
2. Minimum noise fraction hyperspectral data filtering.

Session Plan

Session 1

Data download from USGS and Bhuban, Hyperspectral data download from Weebly

Click here to watch the tutorial Video

Session 2

Python installation in window 10

Click here to watch the tutorial video

Session 3

Spectral Python Basics

Click here to watch the tutorial video

Session 4

Spectral Spectral Algorithms

Click here for more information

Projects

1. Training data set for supervised classification of Hyperspectral data.
2. Obtain spectral signatures for each of the bands of a Hyperspectral data.
3. PCA for dimensionality reduction
4. Unsupervised classification using the Gaussian classifier.

Our Main Teachers

MANOJ KUMAR PADHI working as Assistant Professor, Dept of CSE, Centurion University of Technology and Management, ODISHA . Interested to work on Machine learning,Advanced Java Programming,Deep Learning. Programming Skill: C Programming Data Structure Object Oriented Programming using C++ Formal Language Automata Theory Python Web Development(HTML,CSS,PHP) Database Management Systems Compilers