5 No-Reference Approaches to Image and Video Quality Assessment

Anish Mittal1, Anush K. Moorthy2 and Alan C. Bovik3

1Nokia Research Center, USA

2Qualcomm Inc., USA

3University of Texas at Austin, USA

5.1 Introduction

Visual quality assessment as a field has gained tremendous importance in the past decade, as evinced by the flurry of research activity that has been conducted in leading universities and commercial corporations on topics that fall under its umbrella. The reason for this is the exponential growth of visual data that is being captured, stored, transmitted, and viewed across the world. Driving the previously unfathomable growth in communications, images and videos now form a major chunk of transmitted data. This is not surprising since, from the dawn of time, humans have been visual animals who have preferred images over the written word. One need only look at the amount of area devoted to visual signal processing in the human brain to surmise that vision and its perception forms a major chunk of neurological processing [1, 2]. Hence, researchers have attempted to decode human vision processing and have used models of the visual system for image-processing applications [3–7].

While an image can convey more than a thousand words, transmission of visual content occupies an equivalently large amount of bandwidth in modern communication systems, hence images and videos are compressed before storage or transmission. With increasing resolutions and user expectations, increasingly ...

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