首页> 外文期刊>Journal of the Optical Society of America, A. Optics, image science, and vision >Accurate image quantization adapted to multisource photometric reconstruction for rough textured surface analysis
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Accurate image quantization adapted to multisource photometric reconstruction for rough textured surface analysis

机译:适用于多源光度重建的精确图像量化,用于粗糙的纹理表面分析

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摘要

In classical photometric stereo (PS), a Lambertian surface is illuminated from three distant light sources to recover one normal direction per pixel of the input image. In continuous noiseless cases, PS allows us to reconstruct the textured surfaces in three-dimensions with a high degree of accuracy and a high resolution. In the real world, an image is a digital quantization, a limited and noisy representation of a surface. In this paper, we present an accurate 3D recovery approach for real textured surfaces based on an acquisition PS method. The proposed method uses a sequence of images for each light source to recover an accurate and unlimited representation of a surface. To evaluate the performances of the proposed method, we compare it to other traditional PS methods on real textured surfaces.
机译:在经典的光度立体(PS)中,朗伯表面从三个远处的光源照亮,以恢复输入图像每个像素的法线方向。在连续无噪声的情况下,PS允许我们以高精度和高分辨率在三维上重建纹理化表面。在现实世界中,图像是数字量化,是表面的有限且嘈杂的表示。在本文中,我们提出了一种基于采集PS方法的用于真实纹理表面的准确3D恢复方法。所提出的方法对每个光源使用一系列图像来恢复表面的准确且无限制的表示。为了评估该方法的性能,我们将其与其他在真实纹理表面上的传统PS方法进行了比较。

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