On the Subspace of Image Gradient Orientations

We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data population. We show that replacing intensities with gradient orientations and the $\ell_2$ norm with a cosine-based distance measure offers, to some extend, a remedy to this problem. Our scheme requires the eigen-decomposition of a covariance matrix and is as computationally efficient as standard $\ell_2$ PCA. We demonstrate some of its favorable properties on robust subspace estimation

Locally Non-rigid Registration for Mobile HDR Photography

Image registration for stack-based HDR photography is challenging. If not properly accounted for, camera motion and scene changes result in artifacts in the composite image. Unfortunately, existing methods to address this problem are either accurate, but too slow for mobile devices, or fast, but prone to failing. We propose a method that fills this void: our approach is extremely fast---under 700ms on a commercial tablet for a pair of 5MP images---and prevents the artifacts that arise from insufficient registration quality

Estimation of Large Scalings in Images Based on Multilayer Pseudopolar Fractional Fourier Transform

Accurate estimation of the Fourier transform in log-polar coordinates is a major challenge for phase-correlation based motion estimation. To acquire better image registration accuracy, a method is proposed to estimate the log-polar coordinates coefficients using multilayer pseudopolar fractional Fourier transform (MPFFT). The MPFFT approach encompasses pseudopolar and multilayer techniques and provides a grid which is geometrically similar to the log-polar grid. At low coordinates coefficients the multilayer pseudopolar grid is dense, and at high coordinates coefficients the grid is sparse. As a result, large scalings in images can be estimated, and better image registration accuracy can be achieved. Experimental results demonstrate the effectiveness of the presented method

Capturing 3D textured inner pipe surfaces for sewer inspection

Inspection robots equipped with TV camera technology are commonly used to detect defects in sewer systems. Currently, these defects are predominantly identified by human assessors, a process that is not only time-consuming and costly but also susceptible to errors. Furthermore, existing systems primarily offer only information from 2D imaging for damage assessment, limiting the accurate identification of certain types of damage due to the absence of 3D information. Thus, the necessary solid quantification and characterisation of damage, which is needed to evaluate remediation measures and the associated costs, is limited from the sensory side. In this paper, we introduce an innovative system designed for acquiring multimodal image data using a camera measuring head capable of capturing both color and 3D images with high accuracy and temporal availability based on the single-shot principle. This sensor head, affixed to a carriage, continuously captures the sewer's inner wall during transit. The collected data serves as the basis for an AI-based automatic analysis of pipe damages as part of the further assessment and monitoring of sewers. Moreover, this paper is focused on the fundamental considerations about the design of the multimodal measuring head and elaborates on some application-specific implementation details. These include data pre-processing, 3D reconstruction, registration of texture and depth images, as well as 2D-3D registration and 3D image fusion

Digital image correlation after focused ion beam micro-slit drilling: A new technique for measuring residual stresses in hardmetal components at local scale

A new method has been developed for measuring residual stresses at the surface of hardmetal components with higher spatial resolution than standard X-ray diffraction methods. It is based on measuring the surface displacements produced when stresses are partially released by machining a thin slit perpendicularly to the tested surface. Slit machining is carried out by focused ion beam (FIB). Measurement of the displacement fields around the FIB slit are performed by applying an advanced digital image correlation algorithm based on Fourier analysis with sub-pixel resolution. This method compares SEM images of the same area of the hardmetal surface before and after slitting. The method has been successfully applied to as-ground and femto-laser textured surfaces showing good correlation with the standard sin2 ψ XRD technique. It is concluded that texturing induced by laser pulses in the femtoseconds regime is not perfectly adiabatic, since residual stresses are reduced by 15

Multi-Sensor Image Registration for Remote Sensing under Scale Invariant Feature Transformation

Image registration deals with establishing correspondence between pictures of an equivalent scene or object. A picture registration rule ought to handle the variations introduced by the imaging system capturing the scene. Scale Invariant Feature remodel (SIFT) is a picture registration rule supported native options in a picture. Compared to the previous registration algorithms, SIFT is a lot of sturdy to variations caused by changes in size, illumination, rotation, and viewpoint of the pictures. As a result of its performance, the rule is wide studied, modified, and with success applied in several image and video primarily based applications, within the domains akin to drugs, industry and defense. This paper is associate outcome of in depth study on the state-of-art image registration algorithms supported SIFT. However, directly applying SIFT to remote sensing image registration usually ends up in a really variety of feature points or key points, however, a tiny low number of matching points with a high warning rate. We tend to argue that this is often because of the actual fact that spatial data is not thought about throughout the SIFT-based matching method. This paper proposes a way to enhance SIFT-based matching by taking advantage of neighborhood data. The planned methodology generates a lot of correct matching points because the relative structure in numerous remote sensing pictures area unit virtually static

Digital image correlation after focused ion beam micro-slit drilling: A new technique for measuring residual stresses in hardmetal components at local scale

A new method has been developed for measuring residual stresses at the surface of hardmetal components with higher spatial resolution than standard X-ray diffraction methods. It is based on measuring the surface dis-placements produced when stresses are partially released by machining a thin slit perpendicularly to the tested surface. Slit machining is carried out by focused ion beam (FIB). Measurement of the displacement fields around the FIB slit are performed by applying an advanced digital image correlation algorithm based on Fourier analysis with sub-pixel resolution. This method compares SEM images of the same area of the hardmetal surface before and after slitting. The method has been successfully applied to as-ground and femto-laser textured surfaces showing good correlation with the standard sin2 psi XRD technique. It is concluded that texturing induced by laser pulses in the femtoseconds regime is not perfectly adiabatic, since residual stresses are reduced by 15%