POP Image Fusion -- Derivative Domain Image Fusion without Reintegration

POP Image Fusion -- Derivative Domain Image Fusion without Reintegration
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DOI:
10.1109/iccv.2015.46
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发表时间:
2015-12
期刊:
2015 IEEE International Conference on Computer Vision (ICCV)
影响因子:
--
通讯作者:
G. Finlayson;A. Hayes
G. Finlayson;A. Hayes
中科院分区:
其他
文献类型:
--
作者:
G. Finlayson;A. Hayes

文献摘要

相似文献

在许多应用中,多个图像被融合以形成单个摘要灰度或颜色输出,包括计算摄影(例如RGB-NIR)、扩散张量成像(医学)和遥感。通常,直观地说,图像融合是在导数域中进行的。在这里,一个新的复合融合衍生物被发现,最好的帐户在所有图像的细节,然后得到的梯度场被重新整合。然而,重新整合步骤通常产生包括光晕和弯曲伪影的新细节(未出现在任何输入图像带中)。在本文中,我们避免这些幻觉的细节,避免了重新整合的步骤。我们的工作直接建立在Socolinsky和Wolff的工作上,他们从每个像素的Di Zenzo结构张量中推导出等价的梯度场,该张量被定义为图像雅可比矩阵的内积。我们表明,原始图像的投影到雅可比矩阵的外积(POP)的主特征向量的x-和y-导数产生相同的等效梯度场。在这样做的过程中,我们得到了一个融合的图像,具有我们寻求的衍生结构。当然,这种投影只有在雅可比矩阵具有非零导数的情况下才有意义,因此我们在计算融合图像之前使用双边滤波器扩散投影方向。得到的POP融合图像具有最大的融合细节,但避免了幻觉伪影。实验表明,我们的方法提供了最先进的图像融合性能。
There are many applications where multiple images are fused to form a single summary greyscale or colour output, including computational photography (e.g. RGB-NIR), diffusion tensor imaging (medical), and remote sensing. Often, and intuitively, image fusion is carried out in the derivative domain. Here, a new composite fused derivative is found that best accounts for the detail across all images and then the resulting gradient field is reintegrated. However, the reintegration step generally hallucinates new detail (not appearing in any of the input image bands) including halo and bending artifacts. In this paper we avoid these hallucinated details by avoiding the reintegration step. Our work builds directly on the work of Socolinsky and Wolff who derive their equivalent gradient field from the per-pixel Di Zenzo structure tensor which is defined as the inner product of the image Jacobian. We show that the x-and y-derivatives of the projection of the original image onto the Principal characteristic vector of the Outer Product (POP) of the Jacobian generates the same equivalent gradient field. In so doing, we have derived a fused image that has the derivative structure we seek. Of course, this projection will be meaningful only where the Jacobian has non-zero derivatives, so we diffuse the projection directions using a bilateral filter before we calculate the fused image. The resulting POP fused image has maximal fused detail but avoids hallucinated artifacts. Experiments demonstrate our method delivers state of the art image fusion performance.