In this paper, we propose a simple and effective technique, named extended joint bilateral filter, for reducing color bleeding which is defined as a smearing of the color between areas of strongly contrasting chroma in lossy-compressed images. The color bleeding comes from not only quantization but also sub-sampling in the YCbCr 4:2:0 color format. In order to deal with the two problems simultaneously, we extend the joint bilateral filter formulation by referring all of Y, Cb and Cr components based on a correlation between luma and chroma. As a result, our method achieves both noise reduction and sharpness enhancement for chroma without color edge blurring. Experimental results show that our method is effective in terms of both objective quality and subjective quality.
A method of real-time object detection for video surveillance systems has been developed. The method aims to realize robust object detection by using Radial Reach Correlation (RRC). We also apply a statistical background estimation to cope with dynamic and complex environments. The computational cost of RRC is higher than the simple subtraction method and the background estimation method based on statistical approach needs large memory. It is necessary to reduce the calculation cost in order to apply to an embedded image processing device. Our method is composed of two techniques: fast RRC algorithm and background estimation based on statistical approach with cumulative averaging process. As a result, without deterioration in detection accuracy, the processing time of object detection can be decreased to about 1/4 in comparison with normal RRC.
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