Collaborating filtering using unsupervised learning for image reconstruction from missing data

Collaborating filtering using unsupervised learning for image reconstruction from missing data

Abstract In the image acquisition process, important information in an image can be lost due to noise, occlusion, or even faulty image sensors. Therefore, we often have images with missing and/or corrupted pixels. In this work, we address the problem of image completion using a matrix completion app...

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Bibliographic Details
Main Authors: Oumayma Banouar, Souad Mohaoui, Said Raghay
Format: Article
Language:English
Published: SpringerOpen 2018-11-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Image reconstruction
Bi-clustering
Matrix completion
Unsupervised learning
Prediction
Rank function
Online Access:http://link.springer.com/article/10.1186/s13634-018-0591-3

Internet

http://link.springer.com/article/10.1186/s13634-018-0591-3

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