Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions S-k(x, y)

Paul Bendevis; Edward R. Vrscay

doi:10.1007/978-3-319-11758-4_7

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Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions S-k(x, y)

Conference proceeding

Peer reviewed

Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions S-k(x, y)

Paul Bendevis and Edward R. Vrscay

IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT I, Vol.8814, pp.55-64

Lecture Notes in Computer Science

01/01/2014

DOI: https://doi.org/10.1007/978-3-319-11758-4_7

Abstract

Computer Science

Computer Science, Artificial Intelligence

Computer Science, Theory & Methods

Imaging Science & Photographic Technology

Science & Technology

Technology

We examine the use of individual components of the Structural Similarity image quality measure as criteria for best approximation in terms of orthogonal expansions. We also introduce a family of higher order SSIM-like rational functions.

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Title: Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions S-k(x, y)
Creators - without role: Paul Bendevis - University of Waterloo
Edward R. Vrscay - University of Waterloo
Contributors - without role: A Campilho
M Kamel
Publication Details: IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT I, Vol.8814, pp.55-64
Series: Lecture Notes in Computer Science
Publisher: Springer Nature
Number of pages: 10
Identifiers: 9945431808331
Academic Unit: King Abdullah University of Science & Technology; King Abdulaziz University
Language: English
Resource Type: Conference proceeding