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Monochromatic edge geometry reconstruction through achromatic guidance

机译:通过消色差引导重建单色边缘几何

摘要

Many imaging scenarios involve an achromatic image (e.g., a panchromatic image or a near-infrared image) and one or more concurrently captured monochromatic images (e.g., RGB images captured through a Bayer filter array), and the compositing of these images through de-mosaicing and/or pan-sharpening to generate a high-resolution color image. However, in many such scenarios, the monochromatic images may exhibit distortion of edge geometry, resulting in artifacts and/or color distortions near visual edges of the composite image. However, such distortions may be absent from the achromatic image, and edge geometry may be represented as an intensity gradient among respective neighborhoods of achromatic pixels. Presented herein are techniques for reducing such distortions in monochromatic images through iterative adjustment of monochromatic pixel intensity to reflect the gradients of the neighborhoods of the corresponding achromatic pixels. Convergence of such adjustments produces composite images exhibiting accurately reconstructed edge geometry.
机译:许多成像场景涉及消色差图像(例如,全色图像或近红外图像)和一个或多个同时捕获的单色图像(例如,通过拜耳过滤器阵列捕获的RGB图像),以及通过去噪对这些图像进行合成镶嵌和/或锐化以生成高分辨率的彩色图像。然而,在许多这样的场景中,单色图像可能表现出边缘几何形状的畸变,从而导致在合成图像的视觉边缘附近出现伪像和/或颜色畸变。然而,这种消色差可能在消色差图像中不存在,并且边缘几何形状可以表示为消色差像素的各个邻域之间的强度梯度。本文提出的技术是通过迭代调整单色像素强度以反映相应的消色差像素的邻域的梯度来减少单色图像中的此类失真的技术。这种调整的收敛产生了显示出精确重建的边缘几何形状的合成图像。

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