本文提出一飽和度調整模型基於人眼視覺配合YCbCr色彩模型特性與亮度變化。過去大多數人在做色彩調整時，大都是以分別將亮度與飽和度調整到最好為主要方法，但是經常會發生過飽和的情形發生，使得影像變得較不自然。本文利用曝光補償來模擬當明亮度變化時亮度、飽和度與色相三者之間的關係。根據模擬發現飽和度會隨著亮度變化所改變，也發現其色彩移動模式與YCbCr模型有相呼應的關係。最後，再加上人眼視覺特性來做修正，以達到更好的效果。根據實驗結果可以發現影像色彩的明亮度、對比度與鮮豔度都有所提升，且不會有過飽和的情況發生，影像也較為自然。 This thesis proposes a saturation adjustment method based on human vision with YCbCr color model characteristics and luminance changes. In the traditional color adjustment approach, people tried to separately adjust the luminance and saturation. However, this approach makes the color over-saturate very easily and makes the image look unnatural. In this work we try to use the concept of exposure compensation to simulate the brightness changes and to find the relationship among luminance, saturation, and hue. The simulation indicates that saturation changes with the change of luminance and the simulation also shows there are certain relationships between color variation model and YCbCr color model. Together with all these symptoms, we also include the human vision characteristics to propose a new saturation method to enhance the vision effect of an image. The experimental results show that the proposed approach can make the image have better vivid and contrast. Most important of all, unlike the over-saturation caused by the conventional approach, our approach prevents over-saturation and further makes the adjusted image look natural.
