From Event: SPIE Optical Engineering + Applications, 2017
Broadcasting an outdoor sports event at daytime is a challenging task due to the high contrast that exists between areas in the shadow and light conditions within the same scene. Commercial cameras typically do not handle the high dynamic range of such scenes in a proper manner, resulting in broadcast streams with very little shadow detail. We propose a hardware architecture for real-time shadow removal in high-resolution video, which reduces the shadow effect and simultaneously improves shadow details. The algorithm operates only on the shadow portions of each video frame, thus improving the results and producing more realistic images than algorithms that operate on the entire frame, such as simplified Retinex and histogram shifting. The architecture receives an input in the RGB color space, transforms it into the YIQ space, and uses color information from both spaces to produce a mask of the shadow areas present in the image. The mask is then filtered using a connected components algorithm to eliminate false positives and negatives. The hardware uses pixel information at the edges of the mask to estimate the illumination ratio between light and shadow in the image, which is then used to correct the shadow area. Our prototype implementation simultaneously processes up to 7 video streams of 1920×1080 pixels at 60 frames per second on a Xilinx Kintex-7 XC7K325T FPGA.
Pablo Verdugo, Jorge E. Pezoa, and Miguel Figueroa, "A hardware architecture for real-time shadow removal in high-contrast video," Proc. SPIE 10396, Applications of Digital Image Processing XL, 1039603 (Presented at SPIE Optical Engineering + Applications: August 07, 2017; Published: 19 September 2017); https://doi.org/10.1117/12.2274233.
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