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

Ashish V. Vanmali, Sanket Deshmukh, V. Gadre
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引用次数: 16

Abstract

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.
低复杂度细节保留多曝光图像融合图像平衡曝光
在过去的几年中,多曝光图像融合有了长足的发展,但如何设计一种融合效率高、复杂度低的算法,使其能够在计算能力低的嵌入式平台上实现实时应用,仍然是一个挑战。针对这一需求,本文提出了一种简单、低复杂度的多曝光图像融合算法。该算法是为在曝光范围内均匀分布的图像序列而设计的,没有任何对曝光不足或曝光过度的偏见。融合算法根据输入图像的曝光量为待融合图像的像素分配权重。该融合算法不需要滤波和变换,并且以像素为单位进行,因此在计算复杂度方面具有很高的效率。实验结果表明,我们的算法在视觉上与一些常用的算法相当,而这些算法在计算上要复杂得多。此外,该算法不受输入图像空间错位引起的重影伪影的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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