RS4301 Matlab Programming Syllabus:
RS4301 Matlab Programming Syllabus – Anna University PG Syllabus Regulation 2021
OBJECTIVES
The main objective of this course is to make the student familiar with the basics of MATLAB and usage of various tools in field of geomatics.
UNIT I INTRODUCTION TO MATLAB PROGRAMMING, APPROXIMATIONS AND ERRORS
Basic Syntax – Variables and special variables – Commands – Operators – Data types and display formats – Array operations: array indexing, Scalar-matrix and matrices manipulations – Control structures – M-Files:Scripts and Functions – Solving linear equations – Differentiation and Integration.
UNIT II DATA VISUALIZATION AND MODELLING
Plotting – Plots with multiple lines or functions – Subplots – Annotation: Title, axel title, color, label, data value, tic marks – bar, pie and polar graphs – Surface plots – contour generation – 3D plots – Regression analysis and presentation
UNIT III DIGITAL IMAGE PROCESSING WITH MATLAB
Image types: Grey Scale, RGB and Indexed Color image – Basic Commands for Image reading, writing, displaying, reversing, mirroring, Image shift and image resize (Zoom in and Zoom out) – Image properties extraction – Image type conversions: HSI components extraction, image storage class conversion and graphics file formats conversion – Images in Bit planes – Histogram plotting – Image Noise : Salt and Pepper noise, Gaussian noise, Speckle noise and Periodic noise – Noise removal : methods of low pass and median filtering, outlier, Image averaging and Wiener filter.
UNIT IV SATELLITE IMAGE PROCESSING WITH MATLAB
Pixel selection by pixval and impixel functions – Spatial resolution – Image enhancement: contrast stretching, histogram equalization and thresholding – Morphological operations :structure element, image dilation and erosion – Image convolutions : pillbox and Gaussian low pass filters and Edge enhancement :Sobel, prewitt and canny filters – display techniques : image rotate,image resize, image cropping – colorbar addition – image contouring – NDVI calculation – other image indices – Machine learning with Matlab : Unsupervise, Supervised learning methods – Support vector machine – model interpretability
UNIT V GIS WITH MATLAB
Pixel relationships: neighbors of a pixel, adjacency, path between pixels and distance measures of pixels (Euclidean, Manhattan distance or city-block, shortest m-path distances) – image compaction techniques – Image arithmetic –– Union, intersection and identity of images – Flow direction and flow accumulation calculation – image interpolation – Contour map from DEM –Transforms – affine transformation, collinearity, coplanarity and similarity.
OUTCOMES:
On completion of the course, the student is expected to be able to
CO1 Enable the student to understand basic MatLab functions and to know about the mathematical solvations
CO2 Enable to know about the concepts of visualization
CO3 Learn about the fundamental digital image processing functionalities
CO4 Learn about the tools and commands for satellite images to get proficient in map preparation
CO5 Acquire skills in space based operations using GIS
REFERENCES:
1. Holly Moore, “ MATLAB for Engineers” Third Edition, 2011– Pearson Publications
2. Rafael C.Gonzalez, Richard E.Woods, Steven L.Eddins (2017) : Digital Image processing Using Matlab, Second Edition, MCGraw Hill Eduation,
3. Scott E Umbaugh, (2017), Digital Image Processing and Analysis Applications with Matlab and Cviptools, Taylor and Francis, Third Edition.
4. Giuseppe Ciaburro (2017):MATLAB for machine learning : Practical examples of regression, clustering and neural networks – Functions, Algorithms and use cases, Packt Publishing Limited.
5. Michael Paluszek and Stephanie Thomas , (2019): MATLAB Machine learning recipies: A Problem-Solution Approach.