About this Course

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Advanced Level

Learners are expected to know basic mathematical analysis, linear algebra, information system theory, mathematical methods of optimization.

Approx. 14 hours to complete
English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level

Learners are expected to know basic mathematical analysis, linear algebra, information system theory, mathematical methods of optimization.

Approx. 14 hours to complete
English

Offered by

Placeholder

Moscow Institute of Physics and Technology

Syllabus - What you will learn from this course

Week
1

Week 1

3 hours to complete

Week 1. Image processing pipeline

3 hours to complete
18 videos (Total 50 min), 3 readings, 1 quiz
18 videos
Introduction2m
Background suppression1m
Median filtering1m
Iterative sigma clipping2m
Proposed filter for background suppression1m
Detection of isolated groups of bright pixels2m
Estimation of shape parameters of extracted bright areas for classification as stars or tracks2m
Estimation of stars and satellite tracks parameters2m
Astrometric reduction of the image 4m
Star Catalogue Requirements2m
Determination of correspondences between detected stars and catalogue4m
Hashing the quads2m
Indexing the catalogue3m
Verification of hypothesis6m
Transformation estimation1m
Photometric reduction1m
Examples of processed images6m
3 readings
Lecture Notes of the Course10m
Presentations of the Course10m
Literature1h
1 practice exercise
Test 1.130m
Week
2

Week 2

3 hours to complete

Week 2. Correlation methods for determining the mutual displacement of images

3 hours to complete
5 videos (Total 16 min), 1 reading, 1 quiz
5 videos
Problem statement2m
Algorithm for determining relative image shifts3m
Linear algorithm of shift estimation3m
Quadratic Algorithm of shift estimation4m
1 reading
Literature1h
1 practice exercise
Programming Assignment 2.11h 30m
Week
3

Week 3

3 hours to complete

Week 3. Spatiotemporal methods of filtering observation background

3 hours to complete
4 videos (Total 21 min), 1 reading, 2 quizzes
4 videos
Quality indicators for filtering observation background 1m
Adaptive time filtering algorithms4m
Calculating the filter coefficients as an explicit shift function6m
1 reading
Literature1h
1 practice exercise
Test 3.130m
Week
4

Week 4

6 hours to complete

Week 4. Extraction of spatially resolved point objects from digital image

6 hours to complete
6 videos (Total 21 min), 1 reading, 3 quizzes
6 videos
The general structure of the optimal algorithm2m
Detection of a single object in a fixed window4m
Determination of decision making statistics in the reference points of the image with a symmetric PSF, conjugated with pixel dimensions 4m
Suboptimal algorithm of detection the objects in the reference points of an image2m
Examples of image sequence processing4m
1 reading
Literature1h
3 practice exercises
Programming Assignment 4.11h 30m
Programming Assignment 4.21h 30m
Final Assignment1h 30m

Frequently Asked Questions

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