Technical Program

Paper Detail

Session:Indexing and Retrieval
Time:Wednesday, May 19, 15:30 - 17:30
Presentation: Poster
Topic: Image and Multidimensional Signal Processing: Image and Video Analysis
Authors: Patrick Ndjiki-Nya; Heinrich-Hertz-Institut 
 Oleg Novychny; Heinrich-Hertz-Institut 
 Thomas Wiegand; Heinrich-Hertz-Institut 
Abstract: The underlying assumption of our approach is that the textures in a video scene can be labeled subjectively relevant or irrelevant. Relevant textures are defined as containing subjectively meaningful details, while irrelevant textures can be seen as image content with less important subjective details. We apply this idea to video coding using a texture analyzer and a texture synthesizer. The texture analyzer (encoder side) identifies the texture regions with unimportant subjective details and generates side information for the texture synthesizer (decoder side), which in turn inserts synthetic textures at the specified locations. The focus of this paper is the texture analyzer, which uses multiple MPEG-7 descriptors simultaneously for similarity estimation. The texture analyzer is based on a split and merge segmentation approach. Its current implementation yields an identification rate of up to 96% and an average gain of up to 10% compared to single descriptor usage.

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