A new auto-regressive (AR) model-based algorithm for motion picture restoration

This paper proposes a new AR model-based restoration algorithm which is able to suppress mixed noise processes and recover lost signals in an image sequence. A drawback of an AR model is the limiting size of the block (of pixels) that can be adequately modeled. Using a single set of AR coefficients...

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Bibliographic Details
Main Authors: Kalra, S., Chong, M.N., Krishnan, D.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Bidirectional control
Equations
Exact sciences and technology
Image processing
Image restoration
Information, signal and communications theory
Low pass filters
Motion estimation
Motion pictures
Parameter estimation
Predictive models
Signal processing
Signal restoration
Telecommunications and information theory
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Description
Summary:This paper proposes a new AR model-based restoration algorithm which is able to suppress mixed noise processes and recover lost signals in an image sequence. A drawback of an AR model is the limiting size of the block (of pixels) that can be adequately modeled. Using a single set of AR coefficients to restore a large region of missing data will result in a homogenized texture region. In order to overcome this inherent limitation of the AR model, a block-based divide-and-conquer approach is proposed. In addition, a new Gaussian weighting scheme is used to better estimate the AR coefficients for the interpolation process.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1997.595310