一個超高對比場景所產生的影像，很難在傳統的顯示器上能被完整的顯示。受限於人眼對光線的適應能力以及顯示器的硬體架構下，在顯示器上會看不到高對比影像的暗處還有亮處的內容，為了解決這個問題，影像色調重整( tone reproduction )的演算法便應運而生。

在本篇論文中，我們參考了多篇論文，最後採用細節分層截取法( level set method )以及Barladian的演算法來作為基本的架構。 在這個架構下，適當的加入三個步驟便能有效的加強效果，這三個步驟分別是適應性的增易控制( adaptive gain control )、增減曝光運算( dodging-and-burning )以及區域對比的加強( local contrast enhancement )。 經過基本的架構加上這三個步驟的處理之後，所得到的低動態範圍影像不僅可以解決看不到暗處及亮處的問題，也可以保留住更多的細節，使得結果更能夠被接受及令人滿意。

When capturing scene in a real world, traditional display devices would encounter a problem of representing high contrast. It is because the part in the dimmest region or in the brightest region is almost invisible. The causes of this invisible part can be ascribed to two limits—the brightness adaptation of eye and the architecture of display devices. To overcome this problem, tone reproduction algorithms have been designed to clamp the contrast and conform to human visual system.
In this research, we proposed a new algorithm for tone reproduction problems. This new algorithm is based on the level set method and Barladian’s algorithm; we modify the integrated algorithm with adding three more steps. These three steps are (1) adaptive gain control, (2) dodging-and-burning, and (3) local contrast enhancement. With this modified algorithm, the reproduced images not only visibly represents in low dynamic range, but also conserves and reveals more details.

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