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.
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