No reference image quality assessment using fuzzy relational classifier

Authors:
Indrajit De;Jaya Sil
Affiliations:
Department of Information Technology, MCKV Institute of Engineering, Howrah, West Bengal, India;Department of Computer Science and Technology, Bengal Engineering and Science University, Shibpur Howrah, West Bengal, India
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
Year:
2011

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Abstract

Assessing quality of distorted/decompressed images without reference to the original image is a challenging task because extracted features are often inexact and no predefined relation exists between features and visual quality of images. The paper aims at assessing quality of distorted/ decompressed images without any reference to the original image by developing a robust system using fuzzy relational classifier. First impreciseness in feature space of training data is handled using fuzzy clustering method. As a next step, logical relation between the structure of data and the quality of image are established. Quality of a new image is assessed in terms of degree of membership of the pattern in the given classes applying fuzzy relational operator. Finally, a crisp decision is obtained after defuzzification of the membership value.