Open AccessVideo Magnification Techniques: Medical Applications and Comparison of Methods
Author(s) -
Mohammed Sameer Mohsen,
Ahmed Bashar Fakhri,
Nibras Mahmood Ahmed,
Mustafa F. Mahmood,
Saleem Latteef Mohammed
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1105/1/012074
Subject(s) - magnification , computer science , computer vision , video quality , artificial intelligence , pixel , video camera , noise (video) , pyramid (geometry) , video denoising , video processing , video tracking , image (mathematics) , optics , multiview video coding , physics , engineering , metric (unit) , operations management
The unassisted visual system cannot note minute temporal variations in video and image sequences. In many applications, these differences and small signals are highly informative. A new technique used to expose video variations by measuring and amplifying video variations over time in a fixed position (pixel) was used to Eulerian video magnification (EVM). The objective of the study is to investigate and evaluate different processes for the creation and testing of EVM techniques and video quality parameters for each one of those methods. This research employed four new methods; EVM, Riesz pyramid for fast phase-based video magnification (FPBM), phase-based video magnification (PBM), and Enhanced Eulerian video magnification (E2VM). The experimental findings compared with their output for certain enlargement methods; time and quality parameters of image. A new magnification method is required based on the study of the exiting methods, which takes account of noise elimination, video quality and time reduction.