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中文摘要：
对曝光不足的图像和视频进行亮度调整具有重要的理论研究意义和实际应用价值,本文提出一种基于梯度域操作的图像和视频亮度自动调整算法.对于静态图像,算法首先将图像分割为不同的亮度区域;然后分别计算各区域的亮度调整算子;最后通过求解一个梯度约束方程得到结果图像.我们进而将该算法延伸到视频,首先选取若干关键帧并使用上述图像亮度调整算法进行处理;然后对非关键帧进行分割并通过光流算法确定非关键帧上的分割区域与前后关键帧区域的对应关系;最后利用对应关系通过关键帧区域的亮度调整算子以及调整后的亮度指导非关键帧上各区域的亮度调整,并生成结果视频序列.本文算法可以有效处理空间和时间上曝光不足和不均的图像和视频,并能够较好地保持图像、视频的细节纹理信息,实验结果表明了算法的有效性.
英文摘要：
We present a new approach for automatically adjusting the brighmess of under-exposed digital images and video sequence. Our approach employs ＂divide-and-conquer＂ scheme with gradient domain operation. The under-exposed image is first segmented into different regions according to the brightness. We then compute the brightness enhancement function for each region. Finally a constrained energy function on gradient domain is solved for preserving continuity among different regions. The algorithm is further extended to video. Several key frames are selected from the input video. We adjust them using the image brightness adjust- ment algorithm. Afterwards, through optical flow, we fred the relationship of the regions between the key frames and intermediate frames, and use such relation to adjust the brightness of intermediate frames. Our approach works effectively for dealing with spatially non-uniformly exposed image and temporally non-uniformly under-exposed video. Meanwhile, detail information, such as strong structures as well as textures,is faithfully preserved,as demonstrated by experimental results.
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