Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/17140
Title: Machine Learning Approach to Blocking Effect Reduction in Low Bitrate Video
Authors: Stojkovikj, Ana
GJorgjevikj, Dejan 
Ivanovski, Zoran 
Keywords: Image compression
Video compression
Coding schemes
Blocking artifacts
Super-resolution
Dictionary learning methods
Machine learning methods
Issue Date: 2016
Publisher: SpringerNature
Source: Stojkovikj, A., Gjorgjevikj, D., Ivanovski, Z. (2016). Machine Learning Approach to Blocking Effect Reduction in Low Bitrate Video. In: Loshkovska, S., Koceski, S. (eds) ICT Innovations 2015 . ICT Innovations 2015. Advances in Intelligent Systems and Computing, vol 399. Springer, Cham. https://doi.org/10.1007/978-3-319-25733-4_18
Journal: Advances in Intelligent Systems and Computing
Conference: ICT Innovations 2015
Abstract: This work presents an approach for blocking artifacts removal in highly compressed video sequences using an algorithm based on dictionary learning methods. In this approach only the information from the frame content is used, without any additional information from the coded bit-stream. The proposed algorithm adapts the dictionary to the spatial activity in the image, by that avoiding unnecessary blurring of regions of the image containing high spatial frequencies. The algorithms effectiveness is demonstrated using compressed video with fixed block size of 8x8 pixels.
URI: http://hdl.handle.net/20.500.12188/17140
ISSN: 978-3-319-25733-4
DOI: 10.1007/978-3-319-25733-4_18
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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