先前的研究中幾乎使用高動態範圍技術來處理過度曝光的問題，但這種映射技術會大幅度地改變圖像亮度。為了減輕這個缺點，我們提出了一個方法只有著重在處理曝光過度和曝光不足的區域。我們從圖像中提取前景物件，並且將圖像從RGB色彩空間轉換到YCbCr色彩空間來讓亮度和色度通道能夠分開來。接著我們根據鄰近地區傳播的方式來恢復過度曝光的區域。對於曝光不足的問題，我們使用巴特沃斯濾波器來加強在曝光不足區域中被隱藏的細節。為了表示我們提出的方法是有效用的，我們還進行了前景和背景光度測量的實驗，而結果顯示我們的方法不會像之前的研究大幅度地改變光度分布，且修正過後的圖像也有著比較好的影像對比。

To solve the image overexposure problems, most previous studies employed the high dynamic range techniques. However, most of the high dynamic range techniques change image luminance dramatically. We present a method that only focus on processing overexposed and underexposed regions to alleviate the drawbacks on luminance change. We extract foreground objects from the input image and convert the image from the RGB color space to the YCbCr color space to separate the luminance and the chromaticity channels. After that, we recover the overexposed regions based on neighborhood propagation. For solving the underexposure problem, the Butterworth filter is employed to enhance the hidden details in the underexposed regions. To show the effectiveness of the proposed methods, we conduct extensive experiments on foreground and background luminance measurements. The experiment results suggest that the proposed method do not alter the image luminance distributions as much as previous methods and the result images also have superior image contrast.

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