Multi-scale structural similarity index for motion detection | Zendy

Marwa A. Nasr | Zendy; Mohammed Alrahmawy | Zendy; A. S. Tolba | Zendy

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Multi-scale structural similarity index for motion detection

Author(s) -

Marwa A. Nasr,

Mohammed Alrahmawy,

A. S. Tolba

Publication year - 2016

Publication title -

journal of king saud university - computer and information sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.617

H-Index - 33

eISSN - 2213-1248

pISSN - 1319-1578

DOI - 10.1016/j.jksuci.2016.02.004

Subject(s) - similarity (geometry) , structural similarity , artificial intelligence , luminance , computer science , scale (ratio) , contrast (vision) , computer vision , pattern recognition (psychology) , index (typography) , image (mathematics) , image quality , image processing , geography , cartography , world wide web

The most recent approach for measuring the image quality is the structural similarity index (SSI). This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM) in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed

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