Title :
Quality-Aware Video
Author :
Hiremath, Basavaraj ; Li, Qiang ; Wang, Zhou
Author_Institution :
Univ. of Texas at Arlington, Arlington
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
Development in network visual communications has emphasized on the need of objective, reliable and easy-to-use video quality assessment (VQA) systems. This paper introduces a novel idea of quality-aware video (QAV), in which extracted features about the original video sequence are invisibly embedded into the same video data. When such a QAV sequence is distributed over an error-prone network, a network user who receives it can decode the hidden messages and use them to evaluate the quality degradations between the original and the received video sequences. Our first implementation of QAV employs (1) a novel reduced-reference VQA method based on a statistical model of natural video, and (2) a 3D discrete cosine transform-based data hiding algorithm. The proposed approach does not assume any prior knowledge about image distortions, and the simulation results demonstrate its potentials to be generalized for different types and degrees of image distortions.
Keywords :
data encapsulation; discrete cosine transforms; feature extraction; image sequences; security of data; statistical analysis; video coding; watermarking; 3D discrete cosine transform; data hiding; feature extraction; image distortion; network visual communication; statistical model; video coding; video quality assessment system; video sequence; Data encapsulation; Data mining; Decoding; Degradation; Feature extraction; Quality assessment; Telecommunication network reliability; Video compression; Video sequences; Watermarking; data hiding; natural video statistics; quality aware video; reduced reference; video quality assessment;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379348
