Upsampling

About: Upsampling is a research topic. Over the lifetime, 2426 publications have been published within this topic receiving 57613 citations.

Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging

Abstract: 3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast but low-resolution image acquisition and highly detailed but slow image acquisition. Fast imaging is required for targets that move to avoid motion artefacts. This is in particular difficult for fetal MRI. Spatially independent upsampling techniques, which are the state-of-the-art to address this problem, are error prone and disregard contextual information. In this paper we propose a context-sensitive upsampling method based on a residual convolutional neural network model that learns organ specific appearance and adopts semantically to input data allowing for the generation of high resolution images with sharp edges and fine scale detail. By making contextual decisions about appearance and shape, present in different parts of an image, we gain a maximum of structural detail at a similar contrast as provided by high-resolution data. We experiment on $145$ fetal scans and show that our approach yields an increased PSNR of $1.25$ $dB$ when applied to under-sampled fetal data \emph{cf.} baseline upsampling. Furthermore, our method yields an increased PSNR of $1.73$ $dB$ when utilizing under-sampled fetal data to perform brain volume reconstruction on motion corrupted captured data.

Variational Fusion of Time-of-Flight and Stereo Data for Depth Estimation Using Edge-Selective Joint Filtering

Abstract: In this paper, we propose variational fusion of time-of-flight (TOF) and stereo data for depth estimation using edge-selective joint filtering (ESJF). ESJF is able to adaptively select edges for depth upsampling from the TOF depth map, stereo matching-based disparity map, and stereo images. We adopt ESJF to produce high-resolution (HR) depth maps with accurate edge information from low-resolution ones captured by the TOF camera. First, we measure confidences of TOF and stereo data based on a Gaussian function to be used as fusion weights. Then, we upsample the TOF depth map using ESJF and extract vertical and horizontal discontinuity maps from it. Finally, we perform variational fusion of TOF and stereo depth data guided by the discontinuity maps. Experimental results show that the proposed method successfully produces HR depth maps and outperforms the state of the art in preserving edges and removing noise.

Adaptive upsampling filters

Abstract: In one embodiment, a video coder for coding video data includes a processor and a memory. The processor selects a filter set from a multiple filter sets for upsampling reference layer video data based at least on a prediction operation mode for enhanced layer video data and upsamples the reference layer video data using the selected filter set. Some of the multiple filter sets have some different filter characteristics from one another, and the upsampled reference layer video data has the same spatial resolution as the enhanced layer video data. The processor further codes the enhanced layer video data based at least on the upsampled reference layer video data and the prediction operation mode. The memory stores the upsampled reference layer video data.

Simultaneous Reactive-Power and Frequency Estimations Using Simple Recursive WLS Algorithm and Adaptive Filtering

Abstract: A new simple approach to the design of digital algorithm for simultaneous reactive-power and frequency estimations of local system is presented. The algorithm is derived using the weighted-least-square method. During the algorithm derivation, a pure sinusoidal voltage model was assumed. Cascade finite-impulse-response (FIR) comb digital filters are used to minimize the noise effect and to eliminate the presence of harmonics effect. The most important point of this paper is the mathematical model that transforms the problem of estimation into an overdetermined set of linear equations. The investigation was simplified because the total similarity to the state of the problem of the active-power and frequency estimations was noticed. The only difference is the adaptive phase shifter applied to the voltage signal. In addition, coefficient-sensitivity problems of the large-order FIR comb cascade structure are overridden by using a multirate (decimation) digital signal processing technique. Even more, by using antialiasing filters, the parameter estimation accuracy is improved. The effectiveness of the proposed techniques is demonstrated by both simulation and experimental results. The algorithm shows a very high level of robustness, as well as high measurement accuracy over a wide range of frequency changes.