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Built-up areas are typical man-made structure in urban environment, and timely and accurately acquiring built-up area layers can provide necessary geo-spatial information for planners and policymakers. In this paper, a data field-based method is proposed for the automated detection of built-up areas from high-resolution satellite images. This method views the local corner features of buildings as...
Ultrasonic virtual source imaging based on adaptive bi-directional point-wise focusing is proposed to improve the resolution and contrast when the depth increases. Firstly, ultrasonic array is divided into sub-arrays, the ultrasonic RF scanning lines are collected using fixed-focusing transmitting and receiving and these focuses are considered as virtual sources. Secondly, these scanning lines are...
Learning-based super-resolution (SR) is a popular SR technique that uses application-specific priors to recover missing high-frequency components in low resolution (LR) images. In this paper, we propose a novel approach for obtaining high-resolution (HR) image with solely a single low-resolution input sea-surface image. It is based on sparse representation via dictionary learning. As the image patch...
An embedded CMOS digital dual tuner for DOCSIS 3.0 and set-top box applications is presented. The dual tuner down-converts a total of ten 6 MHz Annex B channels or eight 8 MHz Annex A channels, for a maximum data rate of 320 Mb/s in Annex B and 400 Mb/s in Annex A mode. The dual tuner exceeds all the stringent SCTE 40 specifications over the 48-1004 MHz bandwidth, without using any external components...
Maximum likelihood (ML) estimation is used during tomosynthesis mammography reconstruction. A single reconstruction involves the processing of high-resolution projection images, which is both compute-intensive and time-consuming. This workload is presently a bottleneck in the accurate diagnosis of breast cancer during screening. This paper presents our parallelization work on an ML algorithm using...
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