Spectral Edge Image Fusion: Theory and Applications
Spectral Edge Image Fusion: Theory and Applications
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DOI：
10.1007/978-3-319-10602-1_5
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
David Connah;M. S. Drew;G. Finlayson
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文献类型：
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作者：
David Connah;M. S. Drew;G. Finlayson
本文介绍了一种新的方法来融合彩色显示器的多维图像。该方法的目标是生成一个输出图像，其梯度匹配的输入尽可能接近。它实现了这一点，在梯度域中使用约束对比度映射范例，其中高维梯度表示的结构张量被映射到低维梯度场的结构张量，该低维梯度场随后被重新整合以生成输出。对输出颜色的约束是由初始RGB渲染提供的，以产生“自然主义”的颜色：我们提供了一个定理，用于将较高的D对比度投影到初始颜色梯度上，使得它们保持接近原始梯度，同时保持精确的高D对比度。这种约束优化的解决方案是封闭形式的，允许一个非常简单，因此快速和有效的算法。我们的方法是通用的，因为它可以将任何N-D图像数据映射到任何M-D输出，并且可以使用相同的基本算法用于各种应用程序。在本文中，我们专注于问题的映射N-D输入到3-D彩色输出。我们目前的结果在三个应用程序：高光谱遥感，融合的彩色和近红外图像，彩色可视化的MRI扩散张量成像。
This paper describes a novel approach to the fusion of multidimensional images for colour displays. The goal of the method is to generate an output image whose gradient matches that of the input as closely as possible. It achieves this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mappedexactlyto that of a low-dimensional gradient field which is subsequently reintegrated to generate an output. Constraints on the output colours are provided by an initial RGB rendering to produce ‘naturalistic’ colours: we provide a theorem for projecting higher-D contrast onto the initial colour gradients such that they remain close to the original gradients whilst maintaining exact high-D contrast. The solution to this constrained optimisation is closed-form, allowing for a very simple and hence fast and efficient algorithm. Our approach is generic in that it can map anyN-D image data to anyM-D output, and can be used in a variety of applications using the same basic algorithm. In this paper we focus on the problem of mappingN-D inputs to 3-D colour outputs. We present results in three applications: hyperspectral remote sensing, fusion of colour and near-infrared images, and colour visualisation of MRI Diffusion-Tensor imaging.