高動態範圍影像(High Dynamic Range Images, HDRI)提供了較以往傳統數位影像更高的動態範圍，目的是為了把真實景象裡的光度質準確地重現。一般傳統低動態範圍(Low Dynamic Range, LDR)顯示器能夠顯示的動態範圍，遠低於高動態範圍影像；使用傳統顯示器來顯示高動態範圍影像，將失去其高動態範圍的效果。為了解決這個問題，色調再生(Tone reproduction)演算法應運而生。色調再生演算法能將高動態範圍影像對應至低動態範圍中，以利於低動態範圍顯示器使用。
本論文提出一個以對數為基礎之適應性色調再生演算法。利用適應性對數轉換將輸入影像的亮度值轉換到對數域，可以解決一般對數轉換時容易造成較亮或較暗區域模糊不清的問題。為了強化影像的對比效果，在區域性對比強化之計算中，利用每一個畫素與其鄰居畫素的亮度值之間的關係，來計算區域性對比強化的權重值以強化影像的對比較果，並且加入一個區域性對比強化調整係數來控制整體影像對比強化的程度。在將高動態範圍對應至低動態範圍的步驟中，為了同時兼具可保留原始影像的視覺對比，和可以根據輸入影像的亮度分布內容調整之優點，本論文使用合併線性對應與直方圖等化對應的快速色調對應處理，不但可以處理亮度分布極端的影像，輸出影像之視覺效果也十分出色。
經過實驗與統計分析，本論文提出之演算法的參數預設值適用於絕大多數的輸入影像。有效率地利用低動態範圍的亮度輸出值使得輸出影像有很好的視覺效果，輸出影像較亮以及較暗處的細節與對比皆有良好的表現，並且保有原始影像的視覺觀感，柔和的區域性對比強化效果更增加了影像的可視度。

High dynamic range (HDR) imaging provides larger dynamic range than traditional digital imaging technology. It aims to rebuild the luminance of real world precisely. The dynamic range of traditional low dynamic range (LDR) monitors is much smaller than HDR images. It will lose the visual effect of HDR when using traditional monitors to display HDR images. In order to solve this problem, researchers propose tone reproduction techniques. Tone reproduction algorithm maps HDR images to LDR images effectively such that LDR monitors can display those images exactly.
In this work, we propose an adaptive logarithmic-based tone reproduction algorithm for HDR images. First, we apply adaptive logarithmic transformation to transform luminance into logarithmic domain. Adaptive logarithmic transformation provides a good solution of the drawback of common logarithmic transformation that the brightest or darkest area usually becomes blurred. In order to enhance the contrast of Images, we perform local contrast enhancement algorithm additionally. By computing the luminance relation between pixels, we give different weight to each pixel to enhance contrast of images. We also add a local contrast enhancement factor as a control mechanism of image quality. Finally, we apply a fast tone mapping process for mapping HDR into LDR, it keeps the advantages of saving original contrast and auto adjustment according to the input images additionally.
Experiment results show this algorithm not only keeps the original contrast, but also enhances local contrast to increase visibility. It also performs well in brighter and darker areas of output images, details of those areas are both clear. Finally, this tone reproduction algorithm with default parameter setting can deal with most input images and works well.

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