The performance of image processing algorithms can be significantly improved by the application of multi-resolution image representation with directional features. Directionlet transform (DT) is one such representatio...
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The performance of image processing algorithms can be significantly improved by the application of multi-resolution image representation with directional features. Directionlet transform (DT) is one such representation which has gained popularity over the past few years as an anisotropic, perfect reconstruction and critically sampled basis function with directional vanishing moments along any two directions. In this study, the authors propose a spatially adaptive image denoising scheme for Gaussian noise based on DT by considering the dependences of the directionlet coefficients across different scales. The image is first decomposed using DT and the coefficients so obtained are modelled using a bivariate heavy tailed pdf' with a local variance parameter to account for inter- and intra-scale dependencies of the coefficients. The DT is made adaptive to the local dominant directions in the image by identifying the dominant directions in the spatially segmented image through the computation of a parameter called directional variance'. Bayesian maximum a posteriori' estimator is then used to compute the noise free coefficients from the bivariate models of the signal and noise. The denoised image is obtained from the transform coefficients, which were modified using the bivariate shrinkage function, using directional information and inverse DT. Experimental results show that the bivariate shrinkage in directionlet domain achieves better performance than that in wavelet domain, in terms of numerical and perceptual quality.
Particle tracking is a fundamental technique for investigating a variety of biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, observing three-dimension...
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Particle tracking is a fundamental technique for investigating a variety of biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, observing three-dimensional (3D) trajectories of particles is in general a challenging task in classical microscopy owing to the limited imaging depth of field of commercial optical microscopes, which represents a serious drawback for the analysis of time-lapse microscopy image data. Therefore, numerous automated particle-tracking approaches have been developed by many research groups around the world. Recently, digital holography (DH) in microscopy has rapidly gained credit as one of the elective techniques for these applications, mainly due to the uniqueness of the DH to provide a posteriori quantitative multiple refocusing capability and phase-contrast imaging. Starting from this paradigm, a huge amount of 3D holographic tracking approaches have been conceived and investigated for applications in various branches of science, including optofluids, microfluidics, biomedical microscopy, cell mechano-trasduction, and cell migration. Since a wider community of readers could be interested in such a review, i.e., not only scientists working in the fields of optics and photonics but also users of particle-tracking tools, it should be very beneficial to provide a complete review of state-of-the-art holographic 3D particle-tracking methods and their applications in bio-microfluidics. (C) 2015 Optical Society of America
A polarization sensitive endoscopic optical frequency domain imaging (PS-OFDI) system with a motorized distal scanning catheter is demonstrated. It employs a passive polarization delay unit to multiplex two orthogonal...
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A polarization sensitive endoscopic optical frequency domain imaging (PS-OFDI) system with a motorized distal scanning catheter is demonstrated. It employs a passive polarization delay unit to multiplex two orthogonal probing polarization states in depth, and a polarization diverse detection unit to detect interference signal in two orthogonal polarization channels. Per depth location four electro-magnetic field components are measured that can be represented in a complex 2x2 field matrix. A Jones matrix of the sample is derived and the sample birefringence is extracted by eigenvalue decomposition. The condition of balanced detection and the polarization mode dispersion are quantified. A complex field averaging method based on the alignment of randomly pointing field phasors is developed to reduce speckle noise. The variation of the polarization states incident on the tissue due to the circular scanning and catheter sheath birefringence is investigated. With this system we demonstrated imaging of ex vivo chicken muscle, in vivo pig lung and ex vivo human lung specimens. (C)2015 Optical Society of America
This paper presents a depth-based defocus map estimation method from a single camera with multiple off-axis apertures. The proposed estimation algorithm consists of two steps: (i) object distance estimation using off-...
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This paper presents a depth-based defocus map estimation method from a single camera with multiple off-axis apertures. The proposed estimation algorithm consists of two steps: (i) object distance estimation using off-axis apertures and (ii) defocus map estimation based on the object distance. The proposed method can accurately estimate the defocus map using object distances that are well-characterized in a color shift model-based computational camera. Experimental results show that the proposed method outperforms the state-of-the-art defocus estimation methods in the sense of both accuracy and the estimation range. The proposed defocus map estimation method is suitable for multifocusing, refocusing, and extended depth of field (EDoF) systems. (C) 2015 Optical Society of America
Stochastic Optical Fluctuation Imaging (SOFI) is a super-resolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluo...
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Stochastic Optical Fluctuation Imaging (SOFI) is a super-resolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluorescent emitters. SOFI is not based on the identification and localization of single molecules such as in the widely used Photoactivation Localization Microsopy (PALM) or Stochastic Optical Reconstruction Microscopy (STORM), but computes a superresolved image via temporal cumulants from a recorded movie. A technical challenge hereby is that, when directly applying the SOFI algorithm to a movie of raw images, the pixel size of the final SOFI image is the same as that of the original images, which becomes problematic when the final SOFI resolution is much smaller than this value. In the past, sophisticated cross-correlation schemes have been used for tackling this problem. Here, we present an alternative, exact, straightforward, and simple solution using an interpolation scheme based on Fourier transforms. We exemplify the method on simulated and experimental data. (C) 2015 Optical Society of America
Two historical maps of Cebu City dated 1833 and 1873 were digitized and piecewise linearly transformed to align street maps with current Google Maps of the city. The calculated RMS errors of the transformed maps are e...
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ISBN:
(纸本)9781509003600
Two historical maps of Cebu City dated 1833 and 1873 were digitized and piecewise linearly transformed to align street maps with current Google Maps of the city. The calculated RMS errors of the transformed maps are established to be comparable with other studies. Disappearance of water basins and river path changes were observed in the current map. Overlaying a flood hazard map on the transformed historical maps reveals a correlation between sites of reclamation and river path changes with current flood prone areas. Old maps can inform land use planners about ancient water ways that can become flooding hazards if improperly managed.
Ultrasound elastography is able to provide a non-invasive measurement of tissue elasticity properties. Shear wave imaging (SWI) technique is a quantitative method for tissue stiffness assessment. However, traditional ...
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ISBN:
(纸本)9781424492701
Ultrasound elastography is able to provide a non-invasive measurement of tissue elasticity properties. Shear wave imaging (SWI) technique is a quantitative method for tissue stiffness assessment. However, traditional SWI implementations cannot acquire 2D quantitative images of tissue elasticity distribution. In this study, a new shear wave imaging system is proposed and evaluated. Detailed delineation of hardware and image processing algorithms are presented. Programmable devices are selected to support flexible control of the system and the image processing algorithms. Analytic signal based cross-correlation method and a Radon transform based shear wave speed determination method are proposed with parallel computation ability. Tissue mimicking phantom imaging, and in vitro imaging measurements are conducted to demonstrate the performance of the proposed system. The system has the ability to provide a new choice for quantitative mapping of the tissue elasticity, and has good potential to be implemented into commercial ultrasound scanner.
Information graphics, such as graphs and plots, are used in technical documents to convey information to humans and to facilitate greater understanding. Usually, graphics are a key component in a technical document, a...
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ISBN:
(纸本)9781479918058
Information graphics, such as graphs and plots, are used in technical documents to convey information to humans and to facilitate greater understanding. Usually, graphics are a key component in a technical document, as they enable the author to convey complex ideas in a simplified visual format. However, in an automatic text recognition system, which are typically used to digitize documents, the ideas conveyed in a graphical format are lost. We contend that the message or extracted information can be used to help better understand the ideas conveyed in the document. In scientific papers, line plots are the most commonly used graphic to represent experimental results in the form of correlation present between values represented on the axes. The contribution of our work is in the series of image processing algorithms that are used to automatically extract relevant information, including text and plot from graphics found in technical documents. We validate the approach by performing the experiments on a dataset of line plots obtained from scientific documents from computer science conference papers and evaluate the variation of a reconstructed curve from the original curve. Our algorithm achieves a classification accuracy of 91 % across the dataset and successfully extracts the axes from 92 % of line plots. Axes label extraction and line curve tracing are performed successfully in about half the line plots as well.
Dealing with visual data is the key for environmental monitoring tasks in Wireless Multimedia Sensor Networks (WMSNs). Tasks such as object detection, recognition, and/or tracking do require extracting and using the r...
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Dealing with visual data is the key for environmental monitoring tasks in Wireless Multimedia Sensor Networks (WMSNs). Tasks such as object detection, recognition, and/or tracking do require extracting and using the right information from the inherently large amount of visual data. The widely accepted solution of legacy WSNs, transmitting the acquired data to a central base station for further processing, would render a WMSN totally useless because of the unacceptable use of bandwidth and energy. Therefore, we consider the in situ processing as a viable solution for WMSNs. However, processing power and memory capacity restrictions of existing multimedia sensor nodes along with their power consumption are the limiting factors for wide-spread use of in situ processing. Nevertheless, recent technological improvements and introduction of the new ARM cores encourage us to evaluate the imageprocessing capabilities of ARM7/ARM9/ARM11 based micro-controllers for in situ processing in WMSNs. In this work, we first discussed the architectural design differences among the various ARM cores. Then we classified image processing algorithms into three categories. Then, we evaluated the performance of each microcontroller by running a set of basic image processing algorithms necessary for object detection, recognition, and/or tracking. The test results show that ARM11 runs up to 6-30 times faster than ARM9 and ARM7, respectively. Besides, ARM11 consumes up to 5-7 times less energy than ARM9 and ARM7 for the same type of operations.
Isotropic image edge enhancement with high contrast can be achieved using a spiral phase filter (SPF) in a 4f optical system. However, real-time application of edge enhancement with SPF has generally been limited due ...
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Isotropic image edge enhancement with high contrast can be achieved using a spiral phase filter (SPF) in a 4f optical system. However, real-time application of edge enhancement with SPF has generally been limited due to the requirement of coherent light or complex phase-shifting operation. In this paper, we demonstrate a real-time image edge enhancement method using a SPF and a graphic processing unit (GPU). By implementing the process of virtual spiral phase filtering on GPU, we are able to speed up the whole procedure by more than 8.3x with respect to CPU processing, and ultimately achieve video rate for megapixel images. In particular, our implementation can achieve higher speedup for more multiple images. These developments are increasing the potential for image edge enhancement of moving objects. (C) 2014 Optical Society of America
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