Samsung Electronics Co., Ltd.

Juhyun Cho

Jongseong Choi

Yun-Seong Jang

An auto white balancing method for image data includes calculating block variances for the image data and selecting blocks having a block variance higher than a block variance value. The method further includes selecting patches included in a gray zone defined at a color space, applying a corresponding block variance as a weight to the patches of the gray zone, adjusting a first mean value at the color space, and selecting first patch candidates belong to a first distribution at a luminance domain from among patches selected with reference to the adjusted first mean value. The method further includes selecting a shrunken gray zone corresponding to an anchor point in the gray zone and selecting second patch candidates having a second distribution at a color space and a luminance domain, from among patches included in the shrunken gray zone, and calculating a final gain for the image data by combining a first RGB gain and a second RGB gain respectively extracted from the first patch candidates and the second patch candidates.

Image processing device and auto white balancing method

An image signal processor receives a Bayer image signal from an image sensor and converts the Bayer image signal into a normal image signal. The image signal processor includes a memory configured to store a table including reference brightness values and variation values according to the reference brightness values; a shot noise cancelation unit configured to calculate a reference brightness value of the Bayer image signal, select a variation value in the table of the memory according to the calculated reference brightness value, and perform shot noise cancelling on the Bayer image signal based on the selected variation value to generate a modified Bayer image signal; and an interpolation unit configured to generate the normal image signal by performing interpolation based on the modified Bayer image signal.

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Suwon-si, South Korea

Juhyun Cho