過去，已經出現了多種多視圖圖像的顏色校正方法。然而，由於缺乏利用拼接線上的資訊和在重疊區域內來源像素和目標像素之間的共相關紋理考慮，限制了顏色校正的性能。在這篇論文中，針對多視圖圖像，我們提出了一種基於融合共相關直方圖匹配和拼接線的顏色一致性增強方法，以改進現有的顏色校正方法。首先，對於給定的多視圖圖像，執行一種現有的顏色校正方法。接下來，提出了一種基於梯度幅值的方法，用於安排這些圖像的顏色一致性增強順序。然後，對於所考慮的目標圖像的每個重疊區域，導出基於Correlated Histogram Matching(CHM)的顏色增強函數和基於Stitching Line(SL)的顏色增強函數。使用所獲得的顏色增強函數對所考慮的目標圖像的所有重疊區域進行顏色增強，進一步使用所提出的CHMSL融合方法增強每個目標像素的顏色。基於典型的多視圖圖像資料集，進行了全面的實驗，證明了我們的方法相對於最先進的方法可以實現顯著的客觀和主觀的顏色校正增強效果。

In the past, several color correction methods for multi-view images have been developed. However, due to a lack of consideration with regard to fusing the information on stitching lines and the correlated textures between source and target pixels within the overlapping areas, it limits the color correction performance. For multi-view images, in this thesis, we propose a general color consistency enhancement method using the correlated histogram matching- and stitching line based (CHMSL-based) fusion approach to improve existing color correction methods. Initially, one existing color correction method is performed on the given multi-view images. Next,
a gradient magnitude based approach is proposed to schedule the color consistency enhancement order for these images. Then, for each overlapping area of the considered target image, the CHM based color enhancement function and the SL-based color enhancement function are derived. Using the derived color enhancement functions for all overlapping areas of the considered target image, the color of each target pixel is further enhanced using the proposed CHMSL-based fusion approach. Based on typical multi-view image datasets, comprehensive experiments have been carried out to demonstrate that our method can achieve substantial objective and subjective color correction enhancement effects relative to the state-of-the-art methods.

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