8,543 research outputs found
BLADE: Filter Learning for General Purpose Computational Photography
The Rapid and Accurate Image Super Resolution (RAISR) method of Romano,
Isidoro, and Milanfar is a computationally efficient image upscaling method
using a trained set of filters. We describe a generalization of RAISR, which we
name Best Linear Adaptive Enhancement (BLADE). This approach is a trainable
edge-adaptive filtering framework that is general, simple, computationally
efficient, and useful for a wide range of problems in computational
photography. We show applications to operations which may appear in a camera
pipeline including denoising, demosaicing, and stylization
A review on analysis and synthesis of nonlinear stochastic systems with randomly occurring incomplete information
Copyright q 2012 Hongli Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modeling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly occurring uncertainties, randomly occurring nonlinearities, randomly occurring saturation, randomly missing measurements and randomly occurring quantization. Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system. In this paper, we aim to survey some recent advances on the analysis and synthesis problems for nonlinear stochastic systems with randomly occurring incomplete information. The developments of the filtering, control and fault detection problems are systematically reviewed. Latest results on analysis and synthesis of nonlinear stochastic systems are discussed in great detail. In addition, various distributed filtering technologies over sensor networks are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out. © 2012 Hongli Dong et al.This work was supported in part by the National Natural Science Foundation of China under Grants 61273156, 61134009, 61273201, 61021002, and 61004067, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Science Foundation of the USA under Grant No. HRD-1137732, and the Alexander von Humboldt Foundation of German
Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)
Oxford, UK, 26 August 200
Use of idempotent functions in the aggregation of different filters for noise removal
The majority of existing denoising algorithms obtain good results for a specific noise model, and when it is known previously. Nonetheless, there is a lack in denoising algorithms that can deal with any unknown noisy images. Therefore, in this paper, we study the use of aggregation functions for denoising purposes, where the noise model is not necessary known in advance; and how these functions affect the visual and quantitative results of the resultant images
Design of a Low-Power VLSI Macrocell for Nonlinear Adaptive Video Noise Reduction
A VLSI macrocell for edge-preserving video noise reduction is proposed in the paper. It is based on a nonlinear rational filter enhanced by a noise estimator for blind and dynamic adaptation of the filtering parameters to the input signal statistics. The VLSI filter features a modular architecture allowing the extension of both mask size and filtering directions. Both spatial and spatiotemporal algorithms are supported. Simulation results with monochrome test videos prove its efficiency for many noise distributions with PSNR improvements up to 3.8 dB with respect to a nonadaptive solution. The VLSI macrocell has been realized in a 0.18 m CMOS technology using a standard-cells library; it allows for real-time processing of main video formats, up to 30 fps (frames per second) 4CIF, with a power consumption in the order of few mW
Functional sets with typed symbols: Framework and mixed Polynotopes for hybrid nonlinear reachability and filtering
Verification and synthesis of Cyber-Physical Systems (CPS) are challenging
and still raise numerous issues so far. In this paper, an original framework
with mixed sets defined as function images of symbol type domains is first
proposed. Syntax and semantics are explicitly distinguished. Then, both
continuous (interval) and discrete (signed, boolean) symbol types are used to
model dependencies through linear and polynomial functions, so leading to mixed
zonotopic and polynotopic sets. Polynotopes extend sparse polynomial zonotopes
with typed symbols. Polynotopes can both propagate a mixed encoding of
intervals and describe the behavior of logic gates. A functional completeness
result is given, as well as an inclusion method for elementary nonlinear and
switching functions. A Polynotopic Kalman Filter (PKF) is then proposed as a
hybrid nonlinear extension of Zonotopic Kalman Filters (ZKF). Bridges with a
stochastic uncertainty paradigm are outlined. Finally, several discrete,
continuous and hybrid numerical examples including comparisons illustrate the
effectiveness of the theoretical results.Comment: 21 pages, 8 figure
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