Content-Aware Scalability-Type Selection for Rate Adaptation of Scalable Video

Scalable video coders provide different scaling options, such as temporal, spatial, and SNR scalabilities, where rate reduction by discarding enhancement layers of different scalability-type results in different kinds and/or levels of visual distortion depend on the content and bitrate. This depende...

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Bibliographic Details
Main Authors: M. Reha Civanlar, A. Murat Tekalp, Emrah Akyol
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/2007/10236
Description
Summary:Scalable video coders provide different scaling options, such as temporal, spatial, and SNR scalabilities, where rate reduction by discarding enhancement layers of different scalability-type results in different kinds and/or levels of visual distortion depend on the content and bitrate. This dependency between scalability type, video content, and bitrate is not well investigated in the literature. To this effect, we first propose an objective function that quantifies flatness, blockiness, blurriness, and temporal jerkiness artifacts caused by rate reduction by spatial size, frame rate, and quantization parameter scaling. Next, the weights of this objective function are determined for different content (shot) types and different bitrates using a training procedure with subjective evaluation. Finally, a method is proposed for choosing the best scaling type for each temporal segment that results in minimum visual distortion according to this objective function given the content type of temporal segments. Two subjective tests have been performed to validate the proposed procedure for content-aware selection of the best scalability type on soccer videos. Soccer videos scaled from 600 kbps to 100 kbps by the proposed content-aware selection of scalability type have been found visually superior to those that are scaled using a single scalability option over the whole sequence.
ISSN:1687-6172
1687-6180