Sparse and Redundant Representations and Their Applications in

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Sparse and Redundant Representations and Their Applications in Signal and Image Processing (236862) Section 5 & 6: Image Separation, Inpainting & Super-Resolution Winter Semester, 2017/2018 Michael (Miki) Elad

Meeting Plan Quick review of the material covered Answering questions from the students and getting their feedback Discussing a new material – CSC and the relation to … Deep-Learning Administrative issues

Overview of the Material Image Separation & Inpainting Morphological Component Analysis: The Core Idea Cartoon-Texture Image Separation via a Global Treatment From Separation to Inpainting: A Global Approach Patch-Based Image Separation Patch-Based Image Inpainting Patch-Based Impulse Noise Removal Single Image Super-Resolution Single Image Super-Resolution: First Steps Single Image Super-Resolution: Detailed Algorithm Single Image Super-Resolution: The Overall Algorithm Single Image Super-Resolution: Results Summary Sparseland: What is it all About? Sparseland: What is Still Missing

Your Questions and Feedback

The Convolutional Sparse Coding Model and Connections to Deep-Learning New Material? The Convolutional Sparse Coding Model and Connections to Deep-Learning By: Jeremias Sulam

Administrative Issues Lets talk about: The mid-project is due tonight! Submit through the edX system – upload the files and press “Submit” The Final and Bonus projects, along with all the quizzes should be submitted until next Thursday, February 1st at midnight Next plans ? You will present your research projects to me anytime between NOW and April 19th. The grades will be published soon after

That’s All We hope you enjoyed our course