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Improving Passive 3D Model Reconstruction using Image Enhancement

机译:使用图像增强功能改善被动3D模型重建

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Recently, 3D model reconstruction becomes a reality. That is because of using many algorithms that are implemented as automated tools and the ability to process dozens of images which might be calibrated or uncalibrated. When dealing with uncalibrated images, more processing time is usually required to perform "self-calibration". When using uncalibrated images, the images are usually not in perfect quality due to the uncalibrated nature of the capturing process. For this reason, this paper aims to study the impact of using image enhancement techniques on the quality of the building process of 3D models. This work mainly focus on the contrast of images. After applying the preprocessing procedures, the image sets where used to build the 3D models using three software kits (COLMAP, VSFM and Agisoft Photoscan). The results show that applying histogram equalization enhances the quality of the generated 3D models.
机译:最近,3D模型重建成为现实。这是因为使用了许多实现为自动化工具的算法,并且能够处理可能已校准或未校准的许多图像。当处理未校准的图像时,通常需要更多的处理时间来执行“自校准”。当使用未经校准的图像时,由于捕获过程的未经校准的性质,图像通常质量不佳。因此,本文旨在研究使用图像增强技术对3D模型构建过程质量的影响。这项工作主要集中在图像的对比度上。在应用了预处理程序之后,使用三个软件包(COLMAP,VSFM和Agisoft Photoscan)将图像集用于构建3D模型。结果表明,应用直方图均衡化可以提高生成的3D模型的质量。

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