Correcting saturated pixels in images

This paper proposes a novel method to correct saturated pixels in images. This method is based on the YCbCr color space and separately corrects the chrominance and the luminance of saturated pixels. Dynamic thresholds are adopted to identify saturated pixels, i.e. the thresholds for different images and different color channels are different. So our method can correct not only RAW images but also processed images. Once the saturated pixels are identified, there are three kinds of saturated pixels: 1-channel saturated pixels, 2-channel saturated pixels and 3-channel saturated pixels. They are denoted as Ω1, Ω2 and Ω3 respectively. Different strategies are implemented to these three kinds of regions. The color of saturated pixels in Ω1 is corrected according to their original color and the color of their neighborhood. And the color of saturated pixels in Ω2 and Ω3 is corrected only according to the color of their neighborhood. The luminance of saturated pixels is corrected using the model proposed in this paper. Experiment results show our method is effective in correcting saturated pixels of RAW images and process images.