利用超分辨率技术改善传感器网络中低分辨率图像的特征提取和配准效果

Wai Chong Chia, L. Yeong, S. I. Ch'ng, Yoke Lun Kam
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引用次数: 2

摘要

本文评价了利用多图像和单图像超分辨率来降低低分辨率图像配准误差的效果。使用CMUCam4捕获两组低分辨率图像进行评估。此外,还提出了一种利用从分辨率增强/升级图像中提取的特征点来改善低分辨率图像配准的简化方法。仿真结果表明,在配准前对图像进行增强/上尺度处理有助于降低配准误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks
In this paper, the effect of using multi-image and single-image super-resolution to reduce registration errors of low resolution images is evaluated. Two sets of low resolution images were captured using CMUCam4 to perform the evaluation. Moreover, a simplified method that make use of feature points extracted from resolution enhanced / upscaled images to improve the registration of low resolution images is also presented. The simulation results show that enhancing / upscaling the images in prior to registration does help to reduce the registration errors.
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