Spatial mask and diffusion filtering in surveillance video compression

M. Ryan Bales; Steve E. Watkins

doi:10.1117/12.915378

4 April 2012 Spatial mask and diffusion filtering in surveillance video compression

M. Ryan Bales, Steve E. Watkins

Proceedings Volume 8347, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2012; 83472L (2012) https://doi.org/10.1117/12.915378
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2012, San Diego, California, United States

Abstract

A surveillance-centric video compression algorithm is discussed that exploits a background model, motion estimation, truncated difference correction, and entropy encoding. The algorithm's architecture allows tradeoffs between image quality and compression to target regions of salient activity. A set of window-based filters and heat diffusion PDEs is examined for impact on compression ratio and signal quality. Results show that filtering techniques are effective at reducing certain contributions to the data stream with minimal impact on image quality. Results from other compression codecs are included for comparison. The test set comprises a diverse range of surveillance scenes featuring vehicular and pedestrian traffic.

Citation Download Citation

M. Ryan Bales and Steve E. Watkins "Spatial mask and diffusion filtering in surveillance video compression", Proc. SPIE 8347, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2012, 83472L (4 April 2012); https://doi.org/10.1117/12.915378

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