目前在三維掃描領域，評斷三維物體重建好壞之關鍵，通常只有考慮物體形狀之精準性，而忽略了表面顏色，也是影響觀感重要因素之一。三維掃描物體之表面顏色，來自三維重建時，所記錄之三維貼圖影像上色彩資訊。因此，本論文致力於解決三維貼圖影像色彩問題，進而達到修正三維物體表面顏色之效果。本論文分為兩種實驗，實驗一稱為色彩測量方式，實驗二稱為電腦圖學方式，目的皆為修正三維貼圖影像的色彩資訊。實驗一目的為利用色彩測量方式，藉由校色樣本與測量數值化之標準值，修正三維貼圖影像色彩資訊。三維貼圖影像與平面影像處理的不同之處，在於處理第三維度之亮度訊號與色彩資訊，因此進一步利用校正白球，設計方法修正三維亮度訊號與色彩資訊。實驗結果以具參考意義之色差評價，與亮度訊號分布曲線評價，驗證結果優劣。實驗二目的則是模擬真實光源條件，並設計三維亮度訊號補償函數。利用模擬光源照射於三維物體之渲染結果，有效地補償三維貼圖影像之亮度訊號，實驗結果以明度差與心理實驗評價。

Nowadays, the judgment of the 3D reconstructed object is generally cared about accuracy of the shape, but the quality of the face color is often neglected in 3D scanning field. The color information is one of the most important factors for people while evaluating the object. The face color comes from the recorded 3D texture images while 3D reconstructing. Therefore, this thesis focuses on solving the problem of the color information of the 3D texture images, and correcting the face color further. There are two experiments in this thesis. One is defined as correcting 3D texture images with the method of measuring standard of the color information, the other is defined as correcting the 3D texture images with the method of computer graphics. Both of the purposes of the experiments are correcting the color information of the 3D texture images. The purpose of the experiment 1 is correcting the color information of the 3D texture images with calibration charts and the measured values. The difference of the 3D texture images and the 2D images is the luminance and the color information in the third dimension. Therefore, the calibration ball is used for correcting the luminance and the color information in the third dimension. The results of the experiment 1 are compared with the color difference and evaluated the curves of the luminance distribution. The purpose of the experiment 2 is simulating reality lighting condition, and designing the functions to compensate luminance in the third dimension. Use the rendering of the 3D objects, which is under the simulated lighting conditions, and the designed functions to compensate the luminance of the 3D texture images efficiently. The results of the experiment 2 are evaluated with the luminance difference and psychological experiment.

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