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Low complexity detail preserving multi-exposure image fusion for images with balanced exposure

机译:低复杂度细节,可为曝光均衡的图像保留多曝光图像融合

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摘要

Multi-exposure image fusion has undergone considerable growth in the last few years, but the challenge still remains to design an algorithm which is efficient in fusion yet low in complexity, such that it can be implemented for real time applications on embedded platforms which have low computational power. A simple, low complexity algorithm for multi-exposure image fusion is proposed in this paper to cater to this need. The algorithm is designed for the image sequences that spread evenly over the exposure range, without any bias towards under or overexposedness. The fusion algorithm assigns weights to pixels of images to be fused, based on the exposure of the input images. The fusion algorithm is free from filtering and transformation, and is carried out on per pixel basis, thus making it highly efficient in terms of computational complexity. The experimental results show that our algorithm produces visually comparable results with some of the commonly used algorithms, which are computationally much more complex. Also, the proposed algorithm is immune to ghosting artifacts caused due to spatial misalignment of the input images.
机译:在过去的几年中,多曝光图像融合已经取得了长足的发展,但是仍然面临着挑战,即要设计一种融合效率高但复杂度低的算法,以使其能够在具有低融合度的嵌入式平台上实时应用。计算能力。为了满足这一需求,本文提出了一种简单,低复杂度的多曝光图像融合算法。该算法专为在曝光范围内均匀分布的图像序列而设计,不会对曝光不足或曝光过度产生任何偏见。融合算法根据输入图像的曝光,为要融合的图像像素分配权重。融合算法不受滤波和变换的影响,并且在每个像素的基础上执行,因此使其在计算复杂度方面非常高效。实验结果表明,我们的算法与一些常用算法相比,在视觉上具有可比性,但计算复杂得多。而且,所提出的算法不受由于输入图像的空间未对准引起的重影伪影的影响。

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