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| Multi-exposure image fusion based on well-exposedness assessment |
| JIANG Shen-yu, CHEN Kuo, XU Zhi-hai, FENG Hua-jun, LI Qi, CHEN Yue-ting |
| State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China |
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Abstract Aiming at the problem that digital camera is insufficient in dynamic range when taking pictures of wide dynamic range scenes, a spatial-domain fusion method for multi-exposure images was proposed. Scenes were sampled and exposed repeatedly, and brightness changes of different pixels of the images were analyzed.Then, assessment value was calculated using the Gauss model. The well-exposedness assessment method was applied to sub-areas of the images. Weighted value of each pixel was calculated to eliminate the images block effect. Image sequences that imaged under different exposures were fused into high dynamic range (HDR) images with local adaptive exposure, which extended the dynamic range. Compared with other methods, the proposed method is simple and effective, producing results with better performance in scene details and color information, and even with higher entropy．
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Published: 28 August 2015
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基于曝光适度评价的多曝光图像融合方法
针对数字相机在拍摄宽亮度范围场景时动态范围不足的问题,提出一种高效的多曝光图像融合方法.该方法通过场景的多次采样曝光,分析不同像素的亮暗变化,利用高斯数学模型计算评价数值.将结合图像亮度信息的曝光适度评价方法应用于图像分块区域,并计算每个像素的权重值,消除图像块效应.将不同曝光度下成像的图像序列融合为一幅局部自适应曝光的高动态范围（HDR）图像,实现动态范围扩展.与另外3种方法进行对比分析,结果表明：该方法简便有效,细节纹理与颜色信息具有更强的表现能力,且熵值更高.
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