Resources.md

Image Processing Algorithms and Open Source Libraries in Python

Books

Computer Vision: Algorithms and Applications, Richard Szeliski, 2nd edition, draft, 2021

Computer Vision, Linda Shapiro, George Stockman, 2000

Fundamentals of Image Processing, Ian T. Young et al, Delft University of Technology 1995-2007

Pattern Recognition and Machine Learning, Christopher Bishop, 2006

Statistical Pattern Recognition, Andrew R. Webb, Keith D. Copsey, 3rd Edition, 2011

Pattern Classification, R. Duda, P. Hart, D. Stork, 2001

Introduction to Mulitvariate Statistical Analysis, T.W. Anderson, Stanford U., 2003

Feature Extraction in Computer Vision and Image Processing, Mark Nixon, 2001

Image Segmentation: Principles, Techniques and Applications, Tao Lei, Asoke K. Landi, 2023

Image Co-Segmentation, Avik Hati et al, 2023

Digital Image Processing, Rafael C. Gonzalez, Richard E. Woods, 4th edition, 2018

Principles of Digital Image Synthesis, Vol. 1, Andrew S. Glassner, 1995

Handbook of Image Processing and Computer Vision, Vol1: From Energy to Image, Arcangelo Distante, Cosimo Distante, Springer, 2020

Handbook of Image Processing and Computer Vision, Vol2: From Image to Pattern, Arcangelo Distante, Cosimo Distante, Springer, 2020

Handbook of Image Processing and Computer Vision, Vol3: From Pattern to Object, Arcangelo Distante, Cosimo Distante, Springer, 2020

Handbook of Computer Vision and Applications: Volume 1 Sensors and Imaging, Bernd Jahne, 1999

Handbook of Computer Vision and Applications: Volume 2 Signal Processing and Pattern Recognition, Bernd Jahne, 1999

Discrete Time Signal Processing, Alan Oppenheim, Ronald Schafer, MIT, 2nd Edition, 1999

Computer Vision: Modern Approach, Jean Ponce, David Forsyth, 2nd Ed, 2011

Algorithms for Image Processing and Computer Vision, J. R. Parker, 1996

Markov Chains: Gibbs Fields, Monte Carlo Simulation and Queues, Pierre Bremaud, 1998

Sparse and Redundant Representations: from Theory to Applications in Signal and Image Processing, M. Elad, 2010

Articles and online materials

Edge Detection, Contour Finding, Skeletonizing Algorithms

A Fast Parallel Algorithm for Thinning Digital Patterns, TY Zhang, CY Suen, Comm. of ACM, 1984

Building skeleton models via 3-D medial surface/axis thinning algorithms, TC Lee, RL Kashyap and CN Chu, CVGIP, 1994

scikit-image implementation: skeletonize example

CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching, M. Agrawal et al, 2008

scikit-image implementation: CenSurE feature detector example

Marching Cubes - A High Resolution 3D Surface Construction Algorithm, W.E. Lorensen and H.E. Kline, GE, 1987

scikit-image implementation: contour finding example

Snakes - Active Contour Models, M. Kass et al, IJCV, 1988

scikit-image implementation: active contour model example

Theory of Edge Detection, D. Marr, E. Hildreth, MIT, 1979

Edge Detection: A Statistical Approach, A. Halder et al, ICECT, 2011

Filtering and Blurring

Gaussian blur, Wikipedia

Tutorial on Image Filtering, Serena Yeung, Stanford U., 2015, online document

Spatial Filtering: Laplacian and Laplacian of Gaussian, online document

Image and Pattern Recognition, Matching

Tutorial on Image Recognition, Serena Yeung, Stanford U., 2015, online document

Tutorial on Image Matching, Serena Yeung, Stanford U., 2015, online document

Matching Images by Comparing their Gradient Fields, Daniel Scharstein, 1994

Analysis of focus-measure operators for shape-from-focus, Said Pertuz et al, 2013

Template Matching

Continuous Edge gradient Based template Matching for Articulated Objects, Daniel Mohr et al, 2001

Image Segmentation

Image Segmentation: Principles, Techniques and Applications, Tao Lei, Asoke K. Landi, 2023

Image Co-Segmentation, Avik Hati et al, 2023

Tutorial on Image Segmentation, Serena Yeung, Stanford U., 2015, online document

Inpainting Methods, Techniques, and Algorithms

Variational approaches, Navier-Stokes equations, Stochastic Relaxation

Navier-Stokes, Fluid Dynamics, and Image and Video Inpainting, M. Bertalmio et al, 2001

Image Inpainting, M. Bertalmio, G. Shapiro, V. Caselles, C. Ballester, 1999

An Axiomatic Approach to Image Interpolation, Vicent Caselles et al, 1999

Nonlinear Total Variation Based Noise Removal Algorithms, L. Rudin, S. Osher, E. Fatemi, 1992

Stochastic Relaxation, Gibbs Distributions, and Bayesian Restoration of Images, Stuart Geman and Donald Geman, 1984

Fast Marching Method

An Image Inpainting Technique Based on the Fast Marching Method, Alexandru Telea, 2004

Mathematical Models for Local Non-Texture Inpaintings, T. Chan and J. Shen, 2002

Mathematical Models for Local Deterministic Inpaintings, T. Chan and J. Shen, 2000

Fast marching method, Wikipedia

scikit-fmm: the fast marching method for Python

Evolution, Implementation, and Application of Level Set and Fast Marching Methods for Advancing Fronts, J. A. Sethian, 2000

A Fast Marching Level Set Method for Monotonically Advancing Fronts, J.A. Sethian, 1996

Fast methods for the Eikonal and related Hamilton–Jacobi equations on unstructured meshes, J.A. Sethian, A. Vladimirsky, 1999

Sparse Representations for Image Inpainting

Sparse and Redundant Representations: from Theory to Applications in Signal and Image Processing, M. Elad, 2010

Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA), M. Elad, J.-L. Starck, P. Querre, D.L. Donoho

Optimally sparse representation in general(nonorthogonal) dictionaries via $\mathcal{l}^1$ minimization, David L. Donoho and Michael Elad, 2003

Uncertainty Principles and Ideal Atomic Decomposition, D. Donoho, 2001

Uncertainty Principles and Signal Recovery, D. Donoho, P. Stark, UC Berkeley, 1987

A Generalized Uncertainty Principle and Sparse Representation in Pairs of Bases, Michael Elad and Alfred M. Bruckstein, 2002

Just relax: Convex programming methods for subset selection and sparse approximation, JA Tropp, 2004

Image decomposition via the combination of sparse representations and a variational approach, J.-L. Starck, M. Elad, D.L. Donoho, 2004

Sparse Representations in Unions of Bases, Remi Gribonval, Morten Nielsen, 2002

The Curvelet Transform for Image Denoising, Jean-Luc Starck, Emmanuel J. Candes, and David L. Donoho, 2002

Dynamic Programming, Viscous Flow, Hamilton-Jacobi-Bellman and the Eikonal Equations

The Eikonal Equation, Wikipedia

Discrete Dynamic Programming and Viscosity Solutions of the Bellman Equations, IC Dolcetta, M. Falcone, 1989

Efficient Algorithms for Globally Optimal Trajectories, John Tstsiklis, 1995

Implementation of Efficient Algotihms for Globally Optimal Trajectories, L. C. Polymenakos, D. P. Bertsekas, and J. N. Tsitsiklis, 1998

Hamilton-Jacobi-Bellman Equations and Optimal Control, IC Dolcetta, 1996

Viscosity Solutions of Hamilton-Jacobi Equations and Optimal Control Problems, A. Bressan, 2001

Simplical Dijkstra and A^{*} Algorithms: From Graphs to Continuous Spaces, D.S. Yershov, S.M. LaValle, 2012

Object Detection Techniques and Algorithms

Computer Vision Techniques for Body Detection, Valentina Bianco, online blog, 2021

Blob Detection, Wikipedia

Variational Methods

Optimal Approximations by Piecewise Smooth Functions and Associated Variational Problems, David Mumford, Jayant Shah, 1989

The Bayesian Rationale for Energy Functionals, David Mumford, 1997

Image recovery via total variation minimization and related problems, Antonin Chambolle, Pierre-Louis Lions, 1997

Convergence of an Iterative Method for Total Variation Denoising, David C. Dobson and Curtis R. Vogel, 1997

Introduction to Variational Methods for Graphical Models, Michael I. Jordan et al, UC Berkeley, 1999

Probabilistic Modeling and Reasoning: The Junction Tree Algorithm, David Barber, 2003

Variational Restoration of Nonflat Image Features - Models and Algorithms, T. Chan, J. Seng, 2000

Total Variation Image Restoration with Local Constraints, M. Bertalmio, V. Caselles, B. Rouge, A. Sole, 2002

Image Restoration Subject To Total Variation Constraint, Patrick L. Combettes et al, 2004

Parameter Estimation in TV Image Restoration using Variational Approximation, S. Derin Babacan, A. Katsaggelos, 2008

Dimension Reduction

Modern Dimension Reduction, Philip D. Waggoner, U of Chicago, 2021

Discriminant Analysis

Linear Discriminant Analysis: a Detailed Tutorial, Alaa Tharwat et al, 2017

PCA versus LDA, AM Martinez, AC Kak, 2001

Introduction to Mulitvariate Statistical Analysis, T.W. Anderson, Stanford U., 2003

The Use of Multiple Measurements in Taxonomic Problems, R.A. Fisher, 1933

A Direct LDA algorithm for High-Dimensional Data - with Application to Face-Recognition, H. Yu et al, CMU, 2004

Open Source Libraries

scikit-image

https://scikit-image.org/

opencv

https://docs.opencv.org/4.x/index.html

Classes related to Image Processing Algorithms

Class CS231n: Deep Learning for Computer Vision at Stanford

CS231n: Deep Learning for Computer Vision, Stanford

github repo: https://github.com/cs231n/cs231n.github.io

Class First Principles of Computer Vision at Columbia U., Shree Nayar

Image Formation | Image Sensing | Binary Images, 18 videos Last updated on May 2, 2021

Radiometry and Reflectance | Photometric Stereo | Shape from Shading, 19 videos Last updated on Apr 25, 2021

Optical Flow | Structure from Motion | Object Tracking, 16 videos Last updated on May 25, 2021

Camera Calibration | Uncalibrated Stereo, 2 videos Last updated on May 9, 2021

Depth from Defocus | Active Illumination Methods, 10 videos Last updated on Apr 25, 2021

Appearance Matching, 8 videos Last updated on Jun 3, 2021

Image Processing I | Image Processing II, 12 videos Last updated on Aug 9, 2024

Neural Networks, 9 videos Last updated on Jun 21, 2021

Image Segmentation, 6 videos Last updated on May 25, 2021

Edge Detection | Boundary Detection | SIFT Detector, 16 videos Last updated on Apr 4, 2021

Image Stitching | Face Detection, 12 videos Last updated on Apr 4, 2021