Hayashi Toshiyuki, Tsubouchi Takashi
Graduate School of System and Information Engineering, University of Tsukuba, Tsukuba 305-8573, Japan.
Faculty of System and Information Engineering, University of Tsukuba, Tsukuba 305-8573, Japan.
Sensors (Basel). 2022 Feb 19;22(4):1635. doi: 10.3390/s22041635.
In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future labor shortage and shortage of engineers. In this paper, a method to estimate parameters of motion blur for Point Spread Function (PSF) is mainly discussed, where we assume that there are two main degradation factors caused by the camera, out-of-focus blur and motion blur. A major contribution of this paper is that the parameters can properly be estimated from a sub-image of the object under inspection if the sub-image contains uniform speckled texture. Here, the cepstrum of the sub-image is fully utilized. Then, a filter convoluted PSF which consists of convolution with PSF (motion blur) and PSF (out-of focus blur) can be utilized for deconvolution of the blurred image for sharpening with significant effect. PSF (out-of-focus blur) is a constant function unique to each camera and lens, and can be confirmed before or after shooting. PSF (motion blur), on the other hand, needs to be estimated on a case-by-case basis since the amount and direction of camera movement varies depending on the time of shooting. Previous research papers have sometimes encountered difficulties in estimating the parameters of motion blur because of the emphasis on generality. In this paper, the main object is made of concrete, and on the surface of it there are speckled textures. We hypothesized that we can narrow down the candidates of parameters of motion blur by using these speckled patterns. To verify this hypothesis, we conducted experiments to confirm and examine the following two points using a general-purpose camera used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. 2. Selection method of multiple images to narrow down the candidate minima of the cepstrum. It is novel that the parameters of motion blur can be well estimated by using the unique speckled pattern on the surface of the object.
在本研究中，我们旨在提出一种图像锐化方法，以便能够轻松地从移动相机拍摄的模糊图像中识别混凝土裂缝。本研究有望助力利用广泛的机器人技术实现社会基础设施维护，并解决未来劳动力短缺和工程师短缺的问题。本文主要讨论了一种用于估计点扩散函数（PSF）运动模糊参数的方法，我们假设相机存在两个主要的退化因素，即失焦模糊和运动模糊。本文的一个主要贡献在于，如果子图像包含均匀的斑点纹理，则可以从被检查对象的子图像中正确估计参数。在这里，充分利用了子图像的倒谱。然后，由PSF（运动模糊）和PSF（失焦模糊）卷积组成的滤波器卷积PSF可用于对模糊图像进行去卷积以实现锐化，效果显著。PSF（失焦模糊）是每个相机和镜头特有的常数函数，可以在拍摄前或拍摄后确定。另一方面，由于相机移动的量和方向因拍摄时间而异，PSF（运动模糊）需要根据具体情况进行估计。以往的研究论文有时由于强调通用性，在估计运动模糊参数时遇到困难。在本文中，主要对象是混凝土，其表面有斑点纹理。我们假设可以利用这些斑点图案来缩小运动模糊参数的候选范围。为了验证这一假设，我们使用实际桥梁检测中使用的通用相机进行实验，以确认和检验以下两点：1. 当将混凝土结构特有的孤立点状纹理用作特征点时对倒谱的影响。2. 选择多个图像以缩小倒谱候选最小值的方法。利用物体表面独特的斑点图案能够很好地估计运动模糊参数，这一点很新颖。
