To directly image exoplanets and faint circumstellar disks, the noisy stellar halo must be suppressed to a high level. To achieve this feat, the angular differential imaging observing technique and the least-squares L...
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ISBN:
(纸本)9780819496164
To directly image exoplanets and faint circumstellar disks, the noisy stellar halo must be suppressed to a high level. To achieve this feat, the angular differential imaging observing technique and the least-squares Locally Optimized Combination of Images (LOCI) algorithm have now become the standard in single band direct imaging observations and data reduction. With the development and commissioning of new high-order high-contrast adaptive optics equipped with integral field units, the image subtraction algorithm needs to be modi fied to allow the optimal use of polychromatic images, field-rotated images and archival data. A new algorithm, TLOCI (for Template LOCI), is designed to achieve this task by maximizing a companion signal-to-noise ratio instead of simply minimizing the noise as in the original LOCI algorithm. The TLOCI technique uses an input spectrum and template Point Spread Functions (PSFs, generated from unocculted and unsaturated stellar images) to optimize the reference image least-squares coefficients to minimize the planet self-subtraction, thus maximizing its throughput per wavelength, while simultaneously providing a maximum suppression of the speckle noise. The new algorithm has been developed using on-sky GPI data and has achieved impressive contrast. This paper presents the TLOCI algorithm, on-sky performance, and will discuss the challenges in recovering the planet spectrum with high fidelity.
Three-dimensional (3D) imaging with optical sectioning microscopy uses computational methods to obtain the true fluorescence distribution by ameliorating the effect of defocus, spherical aberration and noise. Inverse ...
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ISBN:
(纸本)9780819498625
Three-dimensional (3D) imaging with optical sectioning microscopy uses computational methods to obtain the true fluorescence distribution by ameliorating the effect of defocus, spherical aberration and noise. Inverse algorithms improve image quality at a fraction of the cost of implementing an optical system by accurate modeling of the imaging system. Good inverse imaging algorithms need to be accurate as well as fast. Better understanding of the image formation model is vital to obtain improved restoration through model-based algorithms. Forward imaging models based on a depth-varying point-spread function (DV-PSF) leads to a substantial improvement in the resulting images because it accounts for depth-induced aberrations present in the imaging system. PSFs at every layer can be represented using their principal components. Computation of the forward imaging model using a principal component analysis (PCA) representation of the DV-PSF requires fewer convolutions than a strata based approach investigated in the past. In this paper we present a new algorithm for maximum likelihood image restoration developed based on a PCA representation of the DV-PSF and an accelerated conjugate gradient (CG) iteration scheme. Results obtained with this PCA-CG algorithm from both simulated and experimental fluorescence microscope data are discussed and compared with results obtained from a CG iteration method based on the strata model and linear interpolation of the DV-PSF. The performance of the PCA-CG algorithms is shown to be promising for practical applications.
The tympanic membrane (ear drum) is a thin tissue film that is stretched between the outer and middle ear. Sound waves travel from outside the ear, and strike the tympanic membrane resulting in its vibration. These vi...
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ISBN:
(纸本)9781628410440
The tympanic membrane (ear drum) is a thin tissue film that is stretched between the outer and middle ear. Sound waves travel from outside the ear, and strike the tympanic membrane resulting in its vibration. These vibrations amplify the sound waves and transmit them to the ossicles (auditory bones). The magnitude of amplification is directly proportional to vibrating area of tympanic membrane. Hence a perforation in this membrane would result in hearing loss. Pure-tone audiometry is the traditional procedure used to detect the amount of hearing loss in a patient. However, it is lengthy and less efficient, as it largely depends on the response of the patient to sound intensity and frequency of pure-tones. We present a relatively more efficient approach to determine hearing loss due to perforated tympanic membrane using image processing techniques. We describe an algorithm that uses unsharp masking to sharpen images of the perforations as well as the tympanic membrane. Then, it converts the image into a binary image using thresholding. A median filter is applied to get rid of the noise component in the image. The ratio of the area of perforation and total area of tympanic membrane will define the percentage of hearing loss. Our approach will eliminate the error introduced due to patient dependency as in the traditional method.
This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landi...
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ISBN:
(纸本)9780819499370
This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.
Commercially available computed tomography (CT) technologies such as iterative reconstruction (IR) have the potential to enable reduced patient doses while maintaining diagnostic image quality. However, systematically...
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ISBN:
(纸本)9780819498267
Commercially available computed tomography (CT) technologies such as iterative reconstruction (IR) have the potential to enable reduced patient doses while maintaining diagnostic image quality. However, systematically determining safe dose reduction levels for IR algorithms is a challenging task due to their non-linear nature. Most attempts to evaluate IR algorithms rely on measurements made in uniform phantoms. Such measurements may overstate the dose reduction potential of IR because they don't account for the complex relationship between anatomical variability and image quality. The purpose of this study was to design anatomically informed textured phantoms for CT performance evaluation. Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom includes intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and imaged on a modern multi-slice clinical CT scanner to assess the noise performance of a commercial IR algorithm in the context of uniform and textured backgrounds. Fifty repeated acquisitions were acquired for each background type and noise was assessed by measuring pixel standard deviation, across the ensemble of repeated acquisitions. For pixels in uniform areas, the IR algorithm reduced noise magnitude (STD) by 60% (compared to FBP). However, for edge pixels, the noise magnitude in the IR images ranged from 20% higher to 40% lower compared to FBP. In all FBP images and in IR images of the uniform phantom, noise appeared to be globally non-stationary (i.e., spatially dependent) but locally stationary (within a reasonably small region of interest). In the IR images of the textured phantoms, the noise was globally and locally non-stationary.
In this paper we are concerned by authentication of printer technologies from microscopic analysis of paper print. At this scale, a print is made of regularly spaced dots whose shape varies from a print to another and...
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ISBN:
(纸本)9780819499455
In this paper we are concerned by authentication of printer technologies from microscopic analysis of paper print. At this scale, a print is made of regularly spaced dots whose shape varies from a print to another and also inside the same document. Thus, dot at the microscopic scale can be considered as an intrinsic signature of printer technologies. Modeling and estimating such a signature for the authentication of printer technologies are really challenging. In this paper, we propose an original modeling of the micrometric scan of document printing. It consists in an extension of the binary response model which takes into account the dot shape. The digital image of a dot is therefore modeled as a set of random pixels distributed following to the so called inverse link function which depends on the center, tone of black, its spreading and its shape. A maximum likelihood estimation algorithm is provided in order to estimate the location, the darkness, the scale and shape parameter of the dot. From experimental results on three different printer technologies (inkjet, laser and offset), we show that the shape parameter is relevant for designing an identification scheme of printer technologies.
Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydro...
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ISBN:
(纸本)9781628413069
Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these algorit
The paper will present a compression algorithm that will allow for both random and non-random sequential binary strings of data to be compressed for storage and transmission of media information. The compression syste...
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ISBN:
(纸本)9780819499226
The paper will present a compression algorithm that will allow for both random and non-random sequential binary strings of data to be compressed for storage and transmission of media information. The compression system has direct applications to the storage and transmission of digital media such as movies, television, audio signals and other visual and auditory signals needed for engineering practicalities in such industries.
A computer algorithm was developed to automatically identify and count melanocytes and keratinocytes in 3D reflectance confocal microscopy (RCM) images of the skin. Computerized pathology increases our understanding a...
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ISBN:
(纸本)9780819498533
A computer algorithm was developed to automatically identify and count melanocytes and keratinocytes in 3D reflectance confocal microscopy (RCM) images of the skin. Computerized pathology increases our understanding and enables prevention of superficial spreading melanoma (SSM). Machine learning involved looking at the images to measure the size of cells through a 2-D Fourier transform and developing an appropriate mask with the erf() function to model the cells. Implementation involved processing the images to identify cells whose image segments provided the least difference when subtracted from the mask. With further simplification of the algorithm, the program may be directly implemented on the RCM images to indicate the presence of keratinocytes in seconds and to quantify the keratinocytes size in the en face plane as a function of depth. Using this system, the algorithm can identify any irregularities in maturation and differentiation of keratinocytes, thereby signaling the possible presence of cancer.
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