Spring 2018 - ENSC 474 D100
Digital/Medical Image Processing (4)
Class Number: 2408
Delivery Method: In Person
Overview
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Course Times + Location:
Jan 3 – Apr 10, 2018: Mon, Wed, 10:30 a.m.–12:20 p.m.
Burnaby -
Exam Times + Location:
Apr 16, 2018
Mon, 3:30–6:30 p.m.
Burnaby
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Instructor:
Parvaneh Saeedi
psaeedi@sfu.ca
1 778 782-4746
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Prerequisites:
((ENSC 180 and ENSC 251) or CMPT 225), and a minimum of 80 units.
Description
CALENDAR DESCRIPTION:
Develops signal processing techniques of wide applicability, presented in the context of processing and analysis of digital images, in particular 2D and3D biomedical images. Covers acquisition, formation and representation of digital images, filtering, enhancement and restoration in both spatial and frequency domains, image segmentation, image registration, and discrete image transforms. Students with credit for ENSC 460/895-Digital Image Processing and Analysis cannot take this course for further credit.
COURSE DETAILS:
Course Outline:
Introduction
- What is digital image processing?
- The origins of digital image processing
- Examples of fields that use digital image processing
- Fundamental steps in digital image processing
Digital Image Fundamentals
- Elements of visual perception
- Light and the electromagnetic spectrum
- Image sensing and acquisition
- Image sampling and quantization
- Some basic relationships between pixels
- Linear and nonlinear operations
Image Enhancement in the Spatial Domain
- Background
- Some Basic Gray Level Transformations
- Histogram Processing
- Enhancement Using Arithmetic/Logic Operations
- Basics of Spatial Filtering
- Smoothing Spatial Filters
- Sharpening Spatial Filters
- Combining Spatial Enhancement Methods
- Image Enhancement in the Frequency Domain
- Introduction to the Fourier Transform and the Frequency Domain
- Smoothing Frequency-Domain Filters
- Sharpening Frequency Domain Filters
- Homomorphic Filtering
Image Restoration
- A Model of the Image Degradation/Restoration Process
- Noise Models
- Restoration in the Presence of Noise Only–Spatial Filtering
- Periodic Noise Reduction by Frequency Domain Filtering
- Linear, Position-Invariant Degradations
- Estimating the Degradation Function
- Constrained Least Squares Filtering
- Geometric Mean Filter
Color Image Processing
- Color Fundamentals
- Color Models
- Pseudocolor Image Processing
- Basics of Full-Color Image Processing
- Color Transformations
- Smoothing and Sharpening
- Color Segmentation
Fundamentals
Feature Detection
Feature Matching
Transform Model Estimation
Evaluation of the Image Registration Accuracy
Morphological Image Processing
- Preliminaries
- Dilation and Erosion
- Opening and Closing
- Some Basic Morphological Algorithms
- Extensions to Gray-Scale Images
Image Segmentation
- Detection of Discontinuities
- Edge Linking and Boundary Detection
- Thresholding
- Region-Based Segmentation
- Level-set based segmentation
Representation and Description
- Boundary descriptors, Fourier Descriptors
- Statistical Moments, Topological Descriptors
- Principal Component Analysis
- Dimensionality Reduction and Recognition using PCA
Registrar Notes:
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