Neural network based auto-white-balancing

A method of auto white balancing, comprising:

• receiving an original image;
• determining an RG logarithmic ratio of a set of red channel values (R) to a set of green channel values (G) of the original image;
• determining a BG logarithmic ratio of a set of blue channel values (B) to the set of green channel values (G) of the original image;
• determining an original two-dimensional (2D) histogram of the original image utilizing the RG logarithmic ratio and the BG logarithmic ratio;
• determining a Gaussian-blur two-dimensional (2D) histogram of a Gaussian-blur image of the original image utilizing the RG logarithmic ratio and the BG logarithmic ratio;
• determining a sharpened two-dimensional (2D) histogram of a sharpened image of the original image utilizing the RG logarithmic ratio and the BG logarithmic ratio;
• determining a Laplacian-edge two-dimensional (2D) histogram of a Laplacian-edge image of the original image utilizing the RG logarithmic ratio and the BG logarithmic ratio;
• and
• determining a white balancing gain utilizing a neural network based on the original 2D histogram, the Gaussian-blur 2D histogram, the sharpened 2D histogram and the Laplacian-edge 2D histogram.