在拍攝夜間有霧霾的影像時，常常因為霧霾及不均勻的地方光源而導致能見度變差及色彩失真。在這些情況下，若是使用常見的日間除霧演算法會因為地方光源的影響而導致大氣光的值變大，並影響到傳輸率之結果，從而導致在夜間霧霾影像進行除霧時會有過度除霧而產生雜訊放大及人工偽影(artifact)的產生。因此本論文提出一個新的夜間除霧演算法，透過修改He[2]等人所提出的暗通道先驗中所使用之大氣光及傳輸率之計算方式，我們首先利用提出的以高斯和侵蝕運算為基礎之暗通到先驗來達到抑制地方光源的影響，再藉由我們所提出修改的傳輸率計算方法，也就是將侵蝕運算子結合傳輸率後再進行細化之運算，而在細化之運算中我們在此篇論文提出了多尺度引導式濾波器的方法，將我們利用上述所改良之傳輸率輸入至我們所提出的多尺度引導式濾波器進行細化，透過上述所提出之三個新穎的改良計算方法，我們可以有效的抑制在對夜間霧霾影像進行除霧時，常常會產生過度除霧而導致過暗之問題，或是產生人工偽影及雜訊過於放大。
在本論文中，除了上述三個在此篇論文所提出對除霧演算法做了改良之外，我們也結合了Guo [22]等人所提出的ICLAHE的方法，並將此ICLAHE做了改良並提出了多尺度裁切限制的ICLAHE，藉由所提出之多尺度裁切限制的ICLAHE，我們可以得到更好的細節資訊，並與上述修改的大氣光及傳輸率做結合，從而得到一個新穎的夜間除霧演算法。在本論文中，會與最新的夜間除霧演算法的結果及計算複雜度做一個比較，並從實驗結果中我們可以得知在此篇論文中所提出的方法有最好之夜間除霧的效果及最有效率之計算速度。

Photographs taken at night time with haze often suffers from poor visibility and color distortion due to uneven local light sources. In this scenario, the common daytime dehazing algorithm results increased atmospheric light due to the influence of local light sources. Due to this, the result of the transmission is affected, resulting in excessive haze removal, noise amplification and artifacts introduction. Consequently, this thesis proposes a new night time dehazing algorithm by modifying the calculation method of atmospheric light and transmission used in the dark channel priors proposed by He[2]. First, the proposed erosion Gaussian-based dark channel is applied to suppress local light sources. Subsequently, a modified transmission calculation method is proposed which combines the erosion operator with the transmission. As the transmission is obtained, the refinement operation is performed. The multi-scale guided filter utilizing improved transmission is applied to the proposed multi-scale guided filters for refinement. Through this improved calculations, the unpleasant issues can be well controlled, including excessive dehazing, excessive darkness, artifacts and excessive amplification of noise.
In addition to the above three improvements on the dehazing algorithm, the ICLAHE proposed by Guo[22] et al is also modified with multi-scale clipping limits to further improve the image quality. With the proposed Multi-scale clipping limit of ICLAHE, details can be obtained. As documented in the experimental results, the proposed method can yield superior performance towards nighttime dehazing effect and of less computational complexity in comparison against the state-of-the-art methods.

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