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cuFFS: A GPU-accelerated code for Fast Faraday rotation measure Synthesis
摘要： Rotation measure (RM) synthesis is a widely used polarization processing algorithm for reconstructing polarized structures along the line of sight. Performing RM synthesis on large datasets produced by telescopes like LOFAR can be computationally intensive as the computational cost is proportional to the product of the number of input frequency channels, the number of output Faraday depth values to be evaluated and the number of lines of sight present in the data cube. The required computational cost is likely to get worse due to the planned large area sky surveys with telescopes like the Low Frequency Array (LOFAR), the Murchison Widefield Array (MWA), and eventually the Square Kilometre Array (SKA). The massively parallel General Purpose Graphical Processing Units (GPGPUs) can be used to execute some of the computationally intensive astronomical image processing algorithms including RM synthesis. In this paper, we present a GPU-accelerated code, called cuFFS or CUDA-accelerated Fast Faraday Synthesis, to perform Faraday rotation measure synthesis. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, our code achieves an increase in speed of up to two orders of magnitude. During testing, we noticed that the disk I/O when using the Flexible Image Transport System (FITS) data format is a major bottleneck and to reduce the time spent on disk I/O, our code supports the faster HDFITS format in addition to the standard FITS format. The code is written in C with GPU-acceleration achieved using Nvidia’s CUDA parallel computing platform. The code is available at https://github.com/sarrvesh/cuFFS.
关键词： Computing methodologies: graphics processors,Techniques: image processing,Techniques: polarimetric,GPGPU,Methods: data analysis
更新于2025-09-23 15:22:29
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[IEEE 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU) - Bhimtal (2018.2.23-2018.2.24)] 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU) - A Method of Segmentation in 3D Medical Image for selection of Region of Interest (ROI).
摘要： In Medical Science manual segmentation process is very costly, time taking and in case of 3D medical images it takes more time and cost in compare to 2D medical images. 3D medical imaging technique provides more precise information of patient for diagnosis and segmentation of 3D medical images is needed for diagnosis and treatment. Here, we present a method for segmentation and selections of Region of Interest (ROI) according to our requirement in one frame and easily analyze image. Our and observe result data from 3D medical computational approach allowed the experts to select the ROI on execution level and free to compare results after each and every execution and identify the best suited result or best image which provides the larger information comparatively others image.
关键词： 3D Medical Imaging,Image Segmentation,Image Processing Techniques
更新于2025-09-23 15:21:21
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[IEEE 2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) - Portici, Italy (2019.10.24-2019.10.26)] 2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) - Critical analysis of instruments and measurement techniques of the shape of trees: Terresrial Laser scanner and Structured Light scanner
摘要： Coastlines, shoals, and reefs are some of the most dynamic and constantly changing regions of the globe. The emergence of high-resolution satellites with new spectral channels, such as the WorldView-2, increases the amount of data available, thereby improving the determination of coastal management parameters. Water-leaving radiance is very difficult to determine accurately, since it is often small compared to the reflected radiance from other sources such as atmospheric and water surface scattering. Hence, the atmospheric correction has proven to be a very important step in the processing of high-resolution images for coastal applications. On the other hand, specular reflection of solar radiation on nonflat water surfaces is a serious confounding factor for bathymetry and for obtaining the seafloor albedo with high precision in shallow-water environments. This paper describes, at first, an optimal atmospheric correction model, as well as an improved algorithm for sunglint removal based on combined physical and image processing techniques. Then, using the corrected multispectral data, an efficient multichannel physics-based algorithm has been implemented, which is capable of solving through optimization the radiative transfer model of seawater for bathymetry retrieval, unmixing the water intrinsic optical properties, depth, and seafloor albedo contributions. Finally, for the mapping of benthic features, a supervised classification methodology has been implemented, combining seafloor-type normalized indexes and support vector machine techniques. Results of atmospheric correction, remote bathymetry, and benthic habitat mapping of shallow-water environments have been validated with in situ data and available bionomic profiles providing excellent accuracy.
关键词： benthic habitat mapping,Atmospheric model,high-resolution multispectral imagery,WorldView-2 (WV2),bathymetry mapping,sunglint,physical and image processing techniques
更新于2025-09-19 17:13:59