20,241 research outputs found
Ensemble Joint Sparse Low Rank Matrix Decomposition for Thermography Diagnosis System
Composite is widely used in the aircraft industry and it is essential for manufacturers to monitor its health and quality. The most commonly found defects of composite are debonds and delamination. Different inner defects with complex irregular shape is difficult to be diagnosed by using conventional thermal imaging methods. In this paper, an ensemble joint sparse low rank matrix decomposition (EJSLRMD) algorithm is proposed by applying the optical pulse thermography (OPT) diagnosis system. The proposed algorithm jointly models the low rank and sparse pattern by using concatenated feature space. In particular, the weak defects information can be separated from strong noise and the resolution contrast of the defects has significantly been improved. Ensemble iterative sparse modelling are conducted to further enhance the weak information as well as reducing the computational cost. In order to show the robustness and efficacy of the model, experiments are conducted to detect the inner debond on multiple carbon fiber reinforced polymer (CFRP) composites. A comparative analysis is presented with general OPT algorithms. Not withstand above, the proposed model has been evaluated on synthetic data and compared with other low rank and sparse matrix decomposition algorithms
Simultaneous real-time visible and infrared video with single-pixel detectors
Conventional cameras rely upon a pixelated sensor to provide spatial resolution. An alternative approach replaces the sensor with a pixelated transmission mask encoded with a series of binary patterns. Combining knowledge of the series of patterns and the associated filtered intensities, measured by single-pixel detectors, allows an image to be deduced through data inversion. In this work we extend the concept of a âsingle-pixel cameraâ to provide continuous real-time video at 10âHz , simultaneously in the visible and short-wave infrared, using an efficient computer algorithm. We demonstrate our camera for imaging through smoke, through a tinted screen, whilst performing compressive sampling and recovering high-resolution detail by arbitrarily controlling the pixel-binning of the masks. We anticipate real-time single-pixel video cameras to have considerable importance where pixelated sensors are limited, allowing for low-cost, non-visible imaging systems in applications such as night-vision, gas sensing and medical diagnostics
The color dependent morphology of the post-AGB star HD161796
Context. Many protoplanetary nebulae show strong asymmetries in their
surrounding shell, pointing to asymmetries during the mass loss phase.
Questions concerning the origin and the onset of deviations from spherical
symmetry are important for our understanding of the evolution of these objects.
Here we focus on the circumstellar shell of the post-AGB star HD 161796. Aims.
We aim at detecting signatures of an aspherical outflow, as well as to derive
the properties of it. Methods. We use the imaging polarimeter ExPo (the extreme
polarimeter), a visitor instrument at the William Herschel Telescope, to
accurately image the dust shell surrounding HD 161796 in various wavelength
filters. Imaging polarimetry allows us to separate the faint, polarized, light
from circumstellar material from the bright, unpolarized, light from the
central star. Results. The shell around HD 161796 is highly aspherical. A clear
signature of an equatorial density enhancement can be seen. This structure is
optically thick at short wavelengths and changes its appearance to optically
thin at longer wavelengths. In the classification of the two different
appearances of planetary nebulae from HST images it changes from being
classified as DUPLEX at short wavelengths to SOLE at longer wavelengths. This
strengthens the interpretation that these two appearances are manifestations of
the same physical structure. Furthermore, we find that the central star is
hotter than often assumed and the relatively high observed reddening is due to
circumstellar rather than interstellar extinction.Comment: Accepted for publication in A&
Application of Pulsed Thermography and Post-processing Techniques for CFRP Industrial Components
AbstractSeveral studies demonstrate the effectiveness of pulsed thermography for detection and visualization of sub-superficial flaws in composites. Continuous improvement of thermal data manipulation makes active thermography an attractive and powerful inspection method for industrial process control and maintenance aims. Therefore, temperature image-processing is the major ongoing challenge in the thermographic research field. However, the particular interest for thermographic inspections is to be more addressed to its simple and relatively fast industrial application; an appropriate image processing tool should be implemented and verified on industrial components, containing manufacturing and in-service defects. In the proposed research, well-established and previously proposed methods were analysed and compared for different defect typology inside three CFRP components. The main goal is not solely focused on establishing the suitable data processing approach, providing detection limits of processed data in terms of damage type, size and distribution. The aim of proposed work is to present detailed examples of thermal imaging methods applied on similar critical defects, evaluating different results among methods in terms of defects mapping capabilities and Tanimoto evaluation criterion, coupled also with the signal-to-noise ratio as assessment of defect detectability
Comparative study of Image Fusion Methods: A Review
As the size and cost of sensors decrease, sensor networks are increasingly becoming an attractive method to collect information in a given area. However, one single sensor is not capable of providing all the required information,either because of their design or because of observational constraints. One possible solution to get all the required information about a particular scene or subject is data fusion.. A small number of metrics proposed so far provide only a rough, numerical estimate of fusion performance with limited understanding of the relative merits of different fusion schemes. This paper proposes a method for comprehensive, objective, image fusion performance characterization using a fusion evaluation framework based on gradient information representation. We give the framework of the overallnbsp system and explain its USAge method. The system has many functions: image denoising, image enhancement, image registration, image segmentation, image fusion, and fusion evaluation. This paper presents a literature review on some of the image fusion techniques for image fusion like, Laplace transform, Discrete Wavelet transform based fusion, Principal component analysis (PCA) based fusion etc. Comparison of all the techniques can be the better approach fornbsp future research
Enhancement of Single and Composite Images Based on Contourlet Transform Approach
Image enhancement is an imperative step in almost every image processing algorithms.
Numerous image enhancement algorithms have been developed for gray scale images
despite their absence in many applications lately. This thesis proposes hew image
enhancement techniques of 8-bit single and composite digital color images. Recently, it
has become evident that wavelet transforms are not necessarily best suited for images.
Therefore, the enhancement approaches are based on a new 'true' two-dimensional
transform called contourlet transform. The proposed enhancement techniques discussed
in this thesis are developed based on the understanding of the working mechanisms of the
new multiresolution property of contourlet transform. This research also investigates the
effects of using different color space representations for color image enhancement
applications. Based on this investigation an optimal color space is selected for both single
image and composite image enhancement approaches. The objective evaluation steps
show that the new method of enhancement not only superior to the commonly used
transformation method (e.g. wavelet transform) but also to various spatial models (e.g.
histogram equalizations). The results found are encouraging and the enhancement
algorithms have proved to be more robust and reliable
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