Learning Multiscale Sparse Representations For Image And Video Restoration Preprint
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Sparse Representation, Modeling and Learning in Visual Recognition
This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers; discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.
Learning Multiscale Sparse Representations for Image and Video Restoration (PREPRINT).
A framework for learning multiscale sparse representations of color images and video with over complete dictionaries is presented in this paper. Following the single-scale grayscale K-SVD algorithm introduced in [1], which formulates the sparse dictionary learning and image representation as an optimization problem efficiently solved via orthogonal matching pursuit and SVD, this proposed multiscale learned representation is obtained based on an efficient quadtree decomposition of the learned dictionary and overlapping image patches. The proposed framework provides an alternative to pre-defined dictionaries such as wavelets, and leads to state-of-the-art results in a number of image and video enhancement and restoration applications. The presentation of the framework here proposed is accompanied by numerous examples demonstrating its practical power.
ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II
Author: Suresh Chandra Satapathy
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-10-19
This volume contains 85 papers presented at CSI 2013: 48th Annual Convention of Computer Society of India with the theme “ICT and Critical Infrastructure”. The convention was held during 13th –15th December 2013 at Hotel Novotel Varun Beach, Visakhapatnam and hosted by Computer Society of India, Vishakhapatnam Chapter in association with Vishakhapatnam Steel Plant, the flagship company of RINL, India. This volume contains papers mainly focused on Data Mining, Data Engineering and Image Processing, Software Engineering and Bio-Informatics, Network Security, Digital Forensics and Cyber Crime, Internet and Multimedia Applications and E-Governance Applications.