KEYWORDS: Wavelets, Video, Wavelet transforms, Digital signal processing, Image processing, Personal protective equipment, Data acquisition, Data processing, Computer programming, Video processing
We propose a real-time system for blur estimation using wavelet decomposition. The system is based on an emerging
multi-core microprocessor architecture (Cell Broadband Engine, Cell BE) known to outperform any available general
purpose or DSP processor in the domain of real-time advanced video processing solutions. We start from a recent
wavelet domain blur estimation algorithm which uses histograms of a local regularity measure called average cone ratio
(ACR). This approach has shown a very good potential for assessing the level of blur in the image yet some important
aspects remain to be addressed in order for the method to become a practically working one. Some of these aspects are
explored in our work. Furthermore, we develop an efficient real-time implementation of the novelty metric and integrate
it into a system that captures live video. The proposed system estimates blur extent and renders the results to the remote
user in real-time.
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