數位影像在拍攝過程中可能受到周遭環境光線變化或不足，導致影像品質降
低。在過去，研究學者提出了很多影像增強方法，然而其演算法大多只能針對單
一亮度或對比做強化。在本篇論文中，提出了一種自動的影像增強方法包含：a)
對比強化法，b)亮度強化法，c)影像分類法。首先我們藉由輸入的影像標準差及
平均亮度來分類輸入的影像，依分類後的影像種類使用不同的影像強化技術。於
亮度強化法中修正了Lee 等人所提出之基於空間變化亮度遮罩(Space Variant
Luminance Map)之彩色影像強化法；在對比強化法中修正了Yun 等學者提出之利
用權重值分配直方圖等化(Weighted Histogram Equalization)，並克服在影像
對比過低時，不易提升輸出影像品質的挑戰。最後本篇論文在實驗中使用
Borland C++ Builder 實現本論文所提出之自動影像增強技術並強化了數張品質
不良之影像，其結果相較於Lee 及Yun 等人所提出之影像增強技術，擁有更佳的
亮度及對比增強效能。

In the digital photographing, the quality of the images may be affected due to the lack or the
changes of the ambient light. In the past, many image enhancement schemes for the image
enhancement are proposed. However, those schemes focus on either the brightness or the contrast of
the image. In the thesis, proposed method to be proposed a scheme for automatic image enhancements,
including the contrast enhancement, the brightness enhancement, and the image classification. First, the
image classification categorize input images according to the standard deviation and the average
luminance, and then take the corresponding schemes to enhance the contrast or the brightness of the
images. In the luminance enhancement, the propose method modified the scheme of the color image
enhancement based on the space variant luminance map, which is proposed by Lee et al. In the contrast
enhancement, our propose method modified the scheme based on the weighted histogram equalization,
which is proposed by Yun et al. Proposed method overcome the challenge that the input image is not
easy to enhance when the input image contrast is extreme poor condition. The proposed scheme of
automatic image enhancements is validated by a Borland C++ program. It should be noted that the
quality of images is better than that of the schemes proposed by Yun et al. and Lee et al.

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