Kalpana Seshadrinathan

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There has recently been a great deal of interest in the development of algorithms that objectively measure the integrity of video signals. Since video signals are being delivered to human end users in an increasingly wide array of applications and products, it is important that automatic methods of video quality assessment (VQA) be available that can assist(More)
We present the results of a recent large-scale subjective study of video quality on a collection of videos distorted by a variety of application-relevant processes. Methods to assess the visual quality of digital videos as perceived by human observers are becoming increasingly important, due to the large number of applications that target humans as the end(More)
—Evaluating the perceptual quality of video is of tremendous importance in the design and optimization of wireless video processing and transmission systems. In an endeavor to emulate human perception of quality, various objective video quality assessment (VQA) algorithms have been developed. However, the only subjective video quality database that exists(More)
Video quality assessment (QA) continues to be an important area of research due to the overwhelming number of applications where videos are delivered to humans. In particular, the problem of temporal pooling of quality sores has received relatively little attention. We observe a hysteresis effect in the subjective judgment of time-varying video quality(More)
Automatic methods to evaluate the perceptual quality of a digital video sequence have widespread applications wherever the end-user is a human. Several objective video quality assessment (VQA) algorithms exist, whose performance is typically evaluated using the results of a subjective study performed by the video quality experts group (VQEG) in 2000. There(More)
This paper studies two increasingly popular paradigms for image quality assessment-Structural SIMilarity (SSIM) metrics and Information Fidelity metrics. The relation of the SSIM metric to Mean Squared Error and Human Visual System (HVS) based models of quality assessment are studied. The SSIM model is shown to be equivalent to models of contrast gain(More)
Quality assessment plays a very important role in almost all aspects of multimedia signal processing such as acquisition, coding, display, processing etc. Several objective quality metrics have been proposed for images, but video quality assessment has received relatively little attention and most video quality metrics have been simple extension of metrics(More)
There is a great deal of interest in methods to assess the perceptual quality of a video sequence in a full reference framework. Motion plays an important role in human perception of video and videos suffer from several artifacts that have to deal with inaccuracies in the representation of motion in the test video compared to the reference. However,(More)
Accurate objective quality metrics are of great potential benefit to the video industry, as they promise the means to evaluate the performance of acquisition, display, coding and communication systems. Although the area of image quality assessment has attained maturity in recent years, video quality assessment still has a long way to go to before it reaches(More)