RESUMEN
In multi-distance coherent diffraction imaging, the task of distance calculation for multi-diffraction images is cumbersome. The information features are hard-to-extract and the region of interest extraction algorithms are difficult to be adopted. A universal salient feature region selection algorithm by using the area with the highest density of corners is proposed to extract the most representative feature region. In addition, equally spaced recording modes and mismatched diffraction distances will result in system noise and destroy image quality. The polydirectional maximum gradient is offered as a sharpness criterion to weigh a quantitative feature for the final pattern. A fast, sensitive, and high-accuracy autofocusing and sample reconstruction can be achieved using only a small number of images while ensuring that morphological properties and quantification of the reconstructions are not compromised. The proposed method is promising for biological and medical dynamic observations for computational imaging systems.
Asunto(s)
Algoritmos , Diagnóstico por ImagenRESUMEN
Online monitoring of the fatigue damage process of A7N01 aluminum alloy base metal and weld seam was conducted based on acoustic emission (AE) and digital microscopic imaging technology. The AE signals were recorded during the fatigue tests and analyzed using the AE characteristic parameter method. Fatigue fracture was observed using scanning electron microscopy (SEM) to analyze the source mechanism of AE. The AE results show that the AE count and rise time can effectively predict the initiation of fatigue microcracks in A7N01 aluminum alloy. The digital image monitoring results of a notch tip verified the prediction of fatigue microcracks using the AE characteristic parameters. In addition, the AE characteristics of the A7N01 aluminum alloy under different fatigue parameters were studied, and the relationships between the AE characteristic values of the base metal and weld seam and the crack propagation rate were calculated using the seven-point recurrence polynomial method. These provide a basis for predicting the remaining fatigue damage in the A7N01 aluminum alloy. The present work indicates that AE technology can be used to monitor the fatigue damage evolution of welded aluminum alloy structures.
RESUMEN
Focusing objects accurately over short time scales is an essential and nontrivial task for a variety of microscopy applications. In this Letter, an autofocusing algorithm using pixel difference with the Tanimoto coefficient (PDTC) is described to predict the focus. Our method can robustly distinguish differences in clarity among datasets. The generated auto-focusing curves have extremely high sensitivity. A dataset of a defocused stack acquired by an Olympus microscope demonstrates the feasibility of our technique. This work can be applied in full-color microscopic imaging systems and is also valid for single-color imaging.
Asunto(s)
Algoritmos , Microscopía , Microscopía/métodosRESUMEN
For lensless diffraction imaging, it is a challenging dilemma to achieve a large field of view (FOV) and high resolution with a small amount of data at the same time. Ptychography can reconstruct the high-resolution image and illumination light simultaneously. But the illumination is limited to a small size by a probe in typical ptychography. For large samples, it takes much time to collect abundant patterns and has strict requirements for the computing power of computers. Another widely applied method, multi-height measurement, can realize a wide FOV with several holograms. But, the recovered image is easily destroyed by the background noise. In this Letter, a lensless diffraction imaging method by three-dimensional scanning is proposed. All positions of the object are different in three directions instead of scanning schemes only on a plane or along the optic axis, so more diversity of diffraction information is obtained. We apply the illumination without the limit of a confined aperture, which means that the imaging FOV of a pattern is equal to the size of the utilized image sensor. In comparison with the multi-height method, our method can separate the illumination background noise from the retrieved object. Consequently, the proposed method realized high resolution and contrast, large FOV, and the removal of background noise simultaneously. Experimental validations and comparisons with other methods are presented.