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Multi-frame motion deblurring using coded exposure imaging with complementary fluttering sequences

机译:使用互补漂移序列的编码曝光成像多帧运动去抑制

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摘要

Motion blurring is one of the most common but unpleasant phenomenons along with the camera imaging process, resulting in image resolution degradation. Coded exposure technique is an effective computational imaging approach to handle with this problem by introducing extra shutter control within the exposure time and help the deblurring problem become well-posed. In this paper, a mull-frame motion deblurring framework is presented using coded exposure imaging with complementary fluttering sequences. A set of complementary sequences are well designed to compensate for the spatial losses due to motion blurring in each frame based on the complementary theory of Golay matrix pair. Hadamard matrix is served as the Golay sequence pair to generate complementary fluttering sequences to capture mull-frame images for the following deblurring processing. The joint modulation transfer function (MTF) of the complementary code sequences has a more flat spectrum curve with smaller variance value and higher MTF value. For mull-frame deblurring implementation, a unified mull-image deblurring framework is performed by introducing Total Variation (TV) regularization prior with each selected code sequence in the complementary set integrated in the energy function. A real imaging system is built and various groups of synthetic and real-world imaging experiments are carried out to verify the effectiveness of the method. Experimental results demonstrate that the deblurrring images obtained by the proposed approach are of high quality with improved objective image evaluation values and better negative artifacts suppression.
机译:运动模糊是相机成像过程中最常见但不愉快的现象之一,导致图像分辨率降级。编码曝光技术是一种通过在曝光时间内引入额外的快门控制来处理该问题的有效计算成像方法,并帮助去掩饰问题变得良好。在本文中,使用具有互补漂流序列的编码曝光成像来呈现Mull帧运动去掩模框架。一组互补序列设计精心齐全,以补偿基于Golay矩阵对的互补理论的每个帧中的运动模糊引起的空间损失。 Hadamard矩阵用作Golay序列对,以产生互补的颤振序列以捕获以下去误紧处理的Mull帧图像。互补码序列的联合调制传递函数(MTF)具有更平坦的频谱曲线,方差值较小和更高的MTF值。对于Mull帧的去掩盖实现,通过在集成在能量函数中的互补集中的每个选定的代码序列之前引入总变化(TV)正则化来执行统一的母图像去孔框架。建立实际成像系统,进行各种合成和实际成像实验,以验证该方法的有效性。实验结果表明,通过所提出的方法获得的DeBlurring图像具有高质量,具有改善的物镜图像评估值和更好的负伪像抑制。

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