Super-resolution reconstruction (SRR) consists in processing an image or a bunch of images to generate a new image of higher spatial resolution. This problem has been intensively studied, but seldom is SRR applied in ...
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ISBN:
(纸本)9783319754178;9783319754161
Super-resolution reconstruction (SRR) consists in processing an image or a bunch of images to generate a new image of higher spatial resolution. This problem has been intensively studied, but seldom is SRR applied in practice for satellite data. In this paper, we briefly review the state of the art on SRR algorithms and we argue that commonly adopted strategies for their evaluation do not reflect the operational conditions. We report our study on assessing the SRR outcome, relying on new quantitative measures. The obtained results allow us to outline the most important research pathways to improve the performance of SRR.
SAR processing usually requires very accurate navigation data, i.e. to form a focused image. The track must be measured within fractions of the centre wavelength. For high frequencies (e.g. X-band) this condition is t...
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ISBN:
(数字)9781510618060
ISBN:
(纸本)9781510618060
SAR processing usually requires very accurate navigation data, i.e. to form a focused image. The track must be measured within fractions of the centre wavelength. For high frequencies (e.g. X-band) this condition is too strict. Even with a cutting-edge motion measurement system, autofocus is a necessity. For low frequencies (e.g. VHF-band) a differential GPS (DGPS) is often an adequate solution (alone). However, for this case, it is actually conceivable to rely on autofocus capability over the motion measurement system. This paper describes how to form a SAR image without support from navigation data. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection realization with six free geometry parameters (per sub-aperture pair). These are tuned step-by-step until a sharp image is obtained. This procedure can compensate for an erroneous geometry (from a focus perspective). The FGA algorithm has been applied successfully on an ultra-wideband (UWB) data set, acquired at VHF-band by the CARABAS 3 system. The track is measured accurately by means of a DGPS. We however adopt and modify a basic geometry model. A linear equidistant flight path at fixed altitude is assumed and adjusted at several resolution levels. With this approach, we emulate a stand-alone processing chain without support from navigation data. The resulting FGA image is compared to a reference image and verified to be focused. This indicates that it is feasible to form a VHF-band SAR image without a motion measurement system.
Ultrasound reflection tomography is widely used to image large complex specimens that are only accessible from a single side, such as well systems and nuclear power plant containment walls. Typical methods for inverti...
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ISBN:
(纸本)9781728112954
Ultrasound reflection tomography is widely used to image large complex specimens that are only accessible from a single side, such as well systems and nuclear power plant containment walls. Typical methods for inverting the measurement rely on delay-and-sum algorithms that rapidly produce reconstructions but with significant artifacts. Recently, model-based reconstruction approaches using a linear forward model have been shown to significantly improve image quality compared to the conventional approach. However, even these techniques result in artifacts for complex objects because of the inherent non-linearity of the ultrasound forward model. In this paper, we propose a non-iterative model-based reconstruction method for inverting measurements that are based on non-linear forward models for ultrasound imaging. Our approach involves obtaining an approximate estimate of the reconstruction using a simple linear back-projection and training a deep neural network to refine this to the actual reconstruction. We apply our method to simulated and experimental ultrasound data to demonstrate dramatic improvements in image quality compared to the delay-and-sum approach and the linear model-based reconstruction approach.
The need to automate tasks has led to state-of-the-art algorithms such as Convolutional Neural Networks (CNNs), which can learn representations from images. CNNs are computationally expensive. Hence, they are mostly i...
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For defogging of pictures, initially it is investigated that if the picture is foggy or clear and for this someone cannot depend upon view of human, so for deciding the picture state as foggy or clear must be comprehe...
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In this paper, modern technologies of adaptive control of welding systems are described. By using robotic welding technical innovations in robotic welding and greater accessibility of sensor control have allowed manua...
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This paper presents a new configurable pruning Gaussian image filter CMOS architecture to address energy efficiency requirements regarding edge detection applications. Low-energy consumption is key for Internet of Thi...
This paper presents a new configurable pruning Gaussian image filter CMOS architecture to address energy efficiency requirements regarding edge detection applications. Low-energy consumption is key for Internet of Things (IoT) devices. Many emerging IoT applications rely on cameras to extract video or image features by running power-hungry computer vision algorithms. The Gaussian image filter is one of the most compute intensive tasks for pre-processing edge detection techniques which are widely adopted in the computer vision domain. Therefore, our proposed 2D Gaussian filter architecture enables: i) a low power and low area overhead runtime configuration scheme based on clock gating technique to prune the Gaussian filter (GF) window size, and ii) run-time capability to balance the tradeoff between edge detection quality and energy efficiency. Our proposed configurable architecture is synthesized and mapped onto 45 nm technology for an ASIC implementation. Results show that for 6 different run-time profiles our proposed configurable architecture provides power dissipation reduction of up to 64% with multiple levels of edge detection quality, which is assessed by considering the performance conformance metric.
Nowadays it becomes more and more critical to process the increasingly large amounts of data in timely manner. In order to meet this requirement and ensure the reliable processing of streaming data, a variety of distr...
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ISBN:
(纸本)9781450364607
Nowadays it becomes more and more critical to process the increasingly large amounts of data in timely manner. In order to meet this requirement and ensure the reliable processing of streaming data, a variety of distributed stream processing architectures and platforms have been developed, which handles the fundamental task of allocating processing tasks to the currently available physical resources and routing streaming data between these resources. However, many stream processingsystems lack an intelligent scheduling mechanism, in which their default schedulers allocate tasks without taking resource demands and availability, or the transfer latency between resources into consideration. Besides stream processing has a strict request for latency. Thus it's important to give latency guarantee for distributed stream processing. In this paper, we propose a new algorithm for stream processing with latency guarantee, the algorithm both consider transfer latency and resource demand in the process of task allocation. Extensive experiments verify the correctness and effectiveness of our approach. Under the condition of satisfying the latency constraints, the heuristic algorithm AHA on average, reduce more than 21.3% and 58.9% resources compared with the greedy and the round-robin algorithms.
With the growing evolution of wireless communication technologies, there is still a need for higher data rates, increased system capacity, and improved service quality. OFDM WiMAX technology is now regarded as one of ...
With the growing evolution of wireless communication technologies, there is still a need for higher data rates, increased system capacity, and improved service quality. OFDM WiMAX technology is now regarded as one of the most common solutions for Broadband Wireless Connectivity in Urban Areas, capable of offering faster implementation and lower costs than standard wired options. This paper proposes effective adaptive algorithm processing with MMSE for use in wireless networks based on SISO and MIMO OFDM WiMAX, enabling network performance to be enhanced in the case of non-LOS wireless communications, which are standard in urban conditions. On the performance of the system, signal attenuation, the effects of several paths l, different mobility speeds and Doppler shift were studied. Combines the adaptive algorithm with MMSE, achieves improved joint channel estimation and signal detection which performs the technique effectively mobile. SNR, MSE and noise components are used to analyses mathematical models of adaptive modulation for transmitting images in SISO and MIMO systems. Simulation results show that the adaptive algorithm with MMSE would improve throughput. For example, when SNR equal 15 dB, the probability of MSE for BPSK based on MIMO principle is equal to 0.0016 with adaptive algorithm. Also, for the same value of SNR, the probability of MSE for BPSK based on MIMO principle is equal to 0.164 without adaptive algorithm. It can also be concluded that when processing signals in a receiving system under conditions of multi-path signal propagation, the use of adaptive algorithms with MMSE has a positive effect on noise immunity.
Human evaluation of SAR is time-consuming and costly. Typically it requires the indirect usability-based assessment of SAR system components or SAR systems from which the images arose. We investigate an assessment sys...
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ISBN:
(纸本)9782874870538
Human evaluation of SAR is time-consuming and costly. Typically it requires the indirect usability-based assessment of SAR system components or SAR systems from which the images arose. We investigate an assessment system which aims at finding digital signal processingalgorithms to simulate, complement and partly replace the human evaluation of SAR images. To better understand the human evaluation, expert SAR interpreters have been asked to solve tasks on SAR images whose different image qualities result from a specific SAR system by varying the parameter settings of one SAR system component. The SAR system component investigated first is the coding system where the spatial and the amplitude resolution are fundamental parameters. In this paper, we describe first results of a human evaluation with expert interpreters where the two coding standards JPEG and HEVC intra coding were evaluated at different spatial resolutions and data rates. The SAR image quality preferred to work with was identified by the interpreters.
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