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Basics of Image Processing

Foreword

Digital images

Introduction
What is a digital image?
Human vision
Image acquisition
Displaying an image
Arithmetic operations
Conclusion

Histogram

Introduction
Histogram
Histogram transformations
Conclusion

Filtering

Introduction
Convolution
Fourier transform
Wavelets
Filtering
Conclusion

Compression

Introduction
Lossless compression
Lossy compression
Conclusion

Interpolation

Interpolation

Segmentation

Introduction
Histogram thresholding
Clustering
Region growing
Watershed
How to evaluate a segmentation?
Conclusion

Mathematical morphology

Introduction
Basic operators
Composition of basic operators
Measure
Conclusion

Restoration

Introduction
Denoising
Deconvolution
Conclusion

Feature detection

Introduction
Matched filter
Edge detection
Corner detection
Line detection
Conclusion

Labs

Lab 1
Lab 2
Lab 3
- Lossy compression
- Interpolation
Lab 4
- Segmentation
Lab 5
- Mathematical morphology
Lab 6
- Denoising
- Deconvolution
Lab 7

In a nutshell

Mathematical optimization
Classification
Deep learning

Appendices

Moodle
Installing and using Python
Glossary
License

.md

Classification

Classification#

🏗️ To do…

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Mathematical optimization

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Deep learning

By Vincent Mazet (University of Strasbourg, France)

© Copyright 2023-2024.

Basics of Image Processing — Vincent Mazet (Université de Strasbourg), 2020-2024 — CC BY-NC 4.0.