Efficient highlight removal of metal surfaces

This paper proposes a novel, simple but fairly effective algorithm based on polynomial calibration function and inpainting method to address the problem of removing large-scale highlights from metal surfaces in an image. Our algorithm works upon an underlying premise that neighboring pixels in space-time with similar intensities should have similar colors. The entire system mainly consists of four components. First, the candidates of highlight areas are identified based on a modified specular free model, and then these candidates are represented in HSV color space. Next, the color channel V is re-calculated by using a luminance calibration formula. Afterwards, highlight areas in H and S color channels are recovered based on a novel inpainting method. Finally, the restored image is obtained by converting the integration results from HSV back to RGB color space. The experimental results on a number of images captured from rail transportation scenario and comparisons with other state-of-the-art approaches demonstrate the effectiveness of the proposed work. An efficient method for removing highlights from metal surfaces in an image.Subjective and objective evaluations on real video surveillance data.Comparisons with other state-of-the-art methods.