Digital Image processing using ENVI

INTRODUCTION

Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Recently, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too. The participants will be taken through fundamental definitions such as image, digital image, and digital image processing. Different sources of digital images, image processing to computer vision and image acquisition and different types of image sensors shall be covered.

DURATION

10 days

COURSE OBJECTIVES

On completion of the course, participants will:

• Be proficient in the use of ENVI
• Understand and be able to undertake geometric referencing of images
• Understand and be able to display image composites for known purposes.
• Know about the potential of and procedures for image processing in a range of application areas
• Proficiency in image processing as outlined in this course is the basis for:
• Developing advanced image processing techniques
• Using image processing in a very wide array of applications with any type of digital image and with a range of software products

COURSE OUTLINE

Module 1

• Basis of Remote Sensing
• Market overview of existing satellites and lunch plan of new satellites (Landsat and Sentinel)
• Prospects for development of remote sensing

Module 2

• Active vs. Passive Remote Sensing
• ENVI main menu;
• Region of Interest tool (ROI)
• Masks

Module 3

• Image registration and orthorectification
• Geometric Correction: image to image and image to map
• Orthorectification;
• Reprojection data.

Module 4

• Georeferencing and mosaicking
• Automatic contrast
• Mosaicking 
• Animation

Module 5

• Vector and raster data
• Editing vector data
• Getting information about vector from attribute table

Module 6

• Spectral Analysis
• Working with spectral libraries
• Spectral Transforms
• Atmospheric Correction

Module 7

• Thematic processing of remote sensing data
• Supervised and Unsupervised Classification;

Module 8

• Post Classification tools
• Accuracy assessment and ground truthing

Module 9

• Change Detection Analysis.

Module 10

• Normalized Difference Vegetation Index (NDVI)
• Mapping