Title: Edge-based singular value decomposition for full reference colour image quality assessment

Authors: Manisha Jadhav; Yogesh H. Dandawate; Narayan Pisharoty

Addresses: Symbiosis International University, Lavale, Pune, Maharashtra, India; Department of Electronics and Telecommunication Engineering, Marathwada Mitra Mandal's College of Engineering, Pune, Maharashtra, India ' Department of Electronics and Telecommunication Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India ' Department of Electronics and Telecommunication Engineering, Symbiosis Institute of Technology, Symbiosis International University, Pune, Maharashtra, India

Abstract: Due to intense use of digital visual aids, image quality plays a crucial role in today's life. Images are subjected to degradations during image acquisition and image processing. This affects their naturalness and usefulness in different applications. Literature shows efforts are made to develop an HVS consistent image quality metric since last few decades. New image quality metrics, extension of existing image quality algorithms and their applications are being developed by researcher's community. Singular value decomposition is one of the measures which are used to quantify the amount of distortion at different distortion levels. Based on the hypothesis that the human eye is adapted to extract edge information from any natural scene, this paper presents a novel approach of introducing edge information in SVD-based image quality metric. The results are compared with SVD-based metric available in related work in literature. Proposed metric outperforms the existing metric. Also, it is extended for evaluation of colour images.

Keywords: image quality; singular value decomposition; SVD; colour model; human visual system; HVS; full reference image quality metric; edge detection.

DOI: 10.1504/IJCVR.2017.086267

International Journal of Computational Vision and Robotics, 2017 Vol.7 No.5, pp.502 - 521

Received: 13 Nov 2014
Accepted: 13 Aug 2015

Published online: 27 Jun 2017 *

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