![]() ![]() Both approaches fulfill our real-time requirements. The proposed paralellization method has been implemented on the Virtex-7 XC7VX690T, Virtex-5 XQR5VFX130 and Virtex-4 XC2VFX60 FPGAs, and on the GT440 and GT610 GPUs, and tested using hyperspectral data from NASA’s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). In this paper, we present both FPGA and OpenCL implementations of the CCSDS 1.2.3 algorithm. ![]() This is where architectures such as Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) can shine best. However, the speed of this lossless compression algorithm is not enough in some real-time scenarios if we use a single-core processor. This produces great amounts of data that require equally big storage, and compression with algorithms such as the Consultative Committee for Space Data Systems (CCSDS) 1.2.3 standard is a must. Hyperspectral imaging is a technology which, by sensing hundreds of wavelengths per pixel, enables fine studies of the captured objects. The second and third experiments demonstrate that AutoHOT can not only accurately characterize the haze intensities but also improve dehazed results, especially for brighter targets, compared to traditional HOT radiometric adjustment. The average overall, user’s and producer’s accuracies of AutoHOT in haze detection can reach 96.4%, 97.6% and 97.5%, respectively. The first experiment confirms that AutoHOT is robust and effective for haze detection. The performances of AutoHOT in haze detection and compensation were evaluated through three experiments with one Landsat-5 TM, one Landsat-7 ETM+ and eight Landsat-8 OLI scenes that encompass diverse landscapes and atmospheric haze conditions. The method is referred to as AutoHOT and characterized with three notable features: a fully automated HOT process, a novel HOT image post-processing tool and a class-based HOT radiometric adjustment method. In this research, a methodology has been developed to fully automate and improve the Haze Optimized Transformation (HOT)-based haze removal. Without an effective method for removing this contamination, most optical remote sensing applications are less reliable. Optical satellite imagery is often contaminated by the persistent presence of clouds and atmospheric haze. Eric marciano radar crack pdf#To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them. PDF is the official format for papers published in both, html and pdf forms.You may sign up for e-mail alerts to receive table of contents of newly released issues.Issues are regarded as officially published after their release is announced to the table of contents alert mailing list. Eric marciano radar crack download#This 30-m Global Food Security-Support Analysis Data, cropland extent product of Africa is available for download () and live view (). This paper integrates novel approaches, involving pixel-based machine learning algorithms with object-based segmentation on the Google Earth Engine cloud, to derive the cropland extent product at 30 m resolution of Africa (2015) using about 36,924 Sentinel-2 and Landsat 8 images. Further, with the population expected to reach 4 billion by the end of this century-from the current 1.2 billion-there is urgent need for accurate, high-resolution cropland maps of Africa. Africa has potential to provide solution to the global food-security challenges of the twenty-first century, given that it is the only continent where land and water are still plentiful for cropland expansion. ![]()
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