- Sur www.coursera.org
Fundamentals of Digital Image and Video Processing
- À son rythme
- Accès libre
- Certificat payant
- 12 séquences
- Niveau Introductif
Détails du cours
Déroulé
- Week 1 - Introduction to Image and Video Processing
In this module we look at images and videos as 2-dimensional (2D) and 3-dimensional (3D) signals, and discuss their analog/digital dichotomy. We will also see how the characteristics of an image changes depending on its placement over the electromagnetic spect... - Week 2 - Signals and Systems
In this module we introduce the fundamentals of 2D signals and systems. Topics include complex exponential signals, linear space-invariant systems, 2D convolution, and filtering in the spatial domain. - Week 3 - Fourier Transform and Sampling
In this module we look at 2D signals in the frequency domain. Topics include: 2D Fourier transform, sampling, discrete Fourier transform, and filtering in the frequency domain. - Week 4 - Motion Estimation
In this module we cover two important topics, motion estimation and color representation and processing. Topics include: applications of motion estimation, phase correlation, block matching, spatio-temporal gradient methods, and fundamentals of color image pro... - Week 5 - Image Enhancement
In this module we cover the important topic of image and video enhancement, i.e., the problem of improving the appearance or usefulness of an image or video. Topics include: point-wise intensity transformation, histogram processing, linear and non-linear noise... - Week 6 - Image Recovery: Part 1
In this module we study the problem of image and video recovery. Topics include: introduction to image and video recovery, image restoration, matrix-vector notation for images, inverse filtering, constrained least squares (CLS), set-theoretic restoration appro... - Week 7 - Image Recovery : Part 2
In this module we look at the problem of image and video recovery from a stochastic perspective. Topics include: Wiener restoration filter, Wiener noise smoothing filter, maximum likelihood and maximum a posteriori estimation, and Bayesian restoration algorith... - Week 8 - Lossless Compression
In this module we introduce the problem of image and video compression with a focus on lossless compression. Topics include: elements of information theory, Huffman coding, run-length coding and fax, arithmetic coding, dictionary techniques, and predictive cod... - Week 9 - Image Compression
In this module we cover fundamental approaches towards lossy image compression. Topics include: scalar and vector quantization, differential pulse-code modulation, fractal image compression, transform coding, JPEG, and subband image compression. - Week 10 - Video Compression
In this module we discus video compression with an emphasis on motion-compensated hybrid video encoding and video compression standards including H.261, H.263, H.264, H.265, MPEG-1, MPEG-2, and MPEG-4. - Week 11 - Image and Video Segmentation
In this module we introduce the problem of image and video segmentation, and discuss various approaches for performing segmentation including methods based on intensity discontinuity and intensity similarity, watersheds and K-means algorithms, and other advanc... - Week 12 - Sparsity
In this module we introduce the notion of sparsity and discuss how this concept is being applied in image and video processing. Topics include: sparsity-promoting norms, matching pursuit algorithm, smooth reformulations, and an overview of the applications.
Prérequis
Aucun.
Intervenants
Aggelos K. Katsaggelos
Joseph Cummings Professor
Department of Electrical Engineering and Computer Science
Éditeur
L'université Northwestern (en anglais : Northwestern University) est une université américaine située à Evanston (juste au nord de la ville de Chicago), dans l'État de l'Illinois aux États-Unis. Elle est l'une des universités les plus prestigieuses du monde, en particulier pour le journalisme, l'économie et le théâtre. L'université comprend deux campus, l'un sur le territoire de la ville d'Evanston (le campus principal), l'autre dans le centre-ville de Chicago.
Plateforme
Coursera est une entreprise numérique proposant des formations en ligne ouverte à tous fondée par les professeurs d'informatique Andrew Ng et Daphne Koller de l'université Stanford, située à Mountain View, Californie.
Ce qui la différencie le plus des autres plateformes MOOC, c'est qu'elle travaille qu'avec les meilleures universités et organisations mondiales et diffuse leurs contenus sur le web.
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