本論文提出一種自動白平衡演算法，該演算法利用圖片中可能的白色區域作為參考，並據此參考區域計算校正色彩三原色(R,G,B)的增益係數，此增益係數將用以修正整張圖片中所有畫素的色彩，本論文提出的演算法基於白色表面的特性，由HSI色彩空間及正規化後的RGB色彩空間中，取出亮度及色度的統計資訊，並依此統計資訊決定在亮度及色度方面的限制條件，所有符合限制條件的色彩將會被認定為圖片中可能的白色區域，由於本論文提中的演算法能夠精確偵測出圖片中的可能白色區域，進而使得計算出的增益係數能夠更精確地修正圖片中的色彩，並且在CIELAB色彩空間中的數值與視覺品質的比較上皆勝過其他以傳統灰色世界演算法(gray world algorithm)為基礎的演算法。

This thesis proposes an automatic white balancing algorithm that takes the potential white color areas in the image as reference to calculate the gain coefficients in the RGB color channels. The estimated gain coefficients are used to correct the colors in the image. According to the properties of the white color surface, the proposed algorithm determines some constraints on luminance and chrominance. These constraints are defined by the statistics from the HSI color space and the normalized RGB color space. The colors in the image that conform to the constraints are considered as the potential white colors. Because the proposed algorithm can detect the potential white color areas exactly, the estimated gain coefficients can correct the colors in the image accurately. The proposed algorithm also outperforms other automatic white algorithms that are based on the gray world algorithm in the comparison of the visual quality and the numerical comparisons.

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