A Bayesian Decision Foreground Extraction Method Combined with Reflected Illumination
A foreground extraction and Bayesian technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as unsatisfactory results, and achieve the effect of fast segmentation, continuous segmentation edges, and increased accuracy.
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[0028] A preferred embodiment of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0029] S1. Grayscale matching transformation
[0030] a) The input image is the luminance generated by one or several point light sources with intensity L on the foreground layer specified by the user, and a point P on the image surface , ρ is the surface BRDF (bidirectional reflectance distribution function) under a given illumination and viewing angle, r is the distance from the illumination point, and θ is the angle between the illumination point and point P. The foreground layer is farther away from the light point, so the foreground objects will have a larger change in exposure, while the background objects will change less.
[0031] b) According to the luminance change calculated after the user input, set the histogram after matching transformation, and specify the probability density on the corresponding gray level for the s...
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