Filters








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Filter fusion

Todd A. Proebsting, Scott A. Watterson
1996 Proceedings of the 23rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '96  
The final step of Filter The second experiment again used five filters.  ...  As an example, we will merge the Evener and the 2ByteSwap filters in Figure 2 . Figure 3 gives their Figure 6 . Figure 7 gives the trimmed graph.  ... 
doi:10.1145/237721.237760 dblp:conf/popl/ProebstingW96 fatcat:4ctx54uflremtnipwcedfgnyae

Fast filtering image fusion

Kun Zhan, Yuange Xie, Haibo Wang, Yufang Min
2017 Journal of Electronic Imaging (JEI)  
An image fusion framework is proposed for different types of multimodal images with fast filtering in the spatial domain.  ...  Third, the weight map is obtained from the multimodal image gradient magnitude and is filtered by a fast structure-preserving filter. Finally, the fused image is composed by using a weighed-sum rule.  ...  Fig. 3 3 Weight map: (a) before filtering, w p ; and (b) after filtering,ŵ p . Algorithm 2 Fast filtering image fusion.  ... 
doi:10.1117/1.jei.26.6.063004 fatcat:xwbyzedzovdexjja6wrntnc5s4

Filter Bank Fusion Frames

Amina Chebira, Matthew Fickus, Dustin G. Mixon
2011 IEEE Transactions on Signal Processing  
In this paper we characterize and construct novel oversampled filter banks implementing fusion frames.  ...  In this work, we first provide polyphase domain characterizations of filter bank fusion frames.  ...  4-channel, 2-downsampled tight filter bank fusion frame.  ... 
doi:10.1109/tsp.2010.2097255 fatcat:ci2vf6t43favpdgwtzsxpbtfyu

Image Fusion With Guided Filtering

Shutao Li, Xudong Kang, Jianwen Hu
2013 IEEE Transactions on Image Processing  
A novel guided filtering-based weighted average technique is proposed to make full use of spatial consistency for fusion of the base and detail layers.  ...  A fast and effective image fusion method is proposed for creating a highly informative fused image through merging multiple images.  ...  Image Fusion with Guided Filtering spatial consistency is not well considered in the fusion process.  ... 
doi:10.1109/tip.2013.2244222 pmid:23372084 fatcat:fjcwxqvhrferhjcnzoayzzz2ea

Cooperative fusion particle filter tracker

LingFeng Wang, HongPing Yan, ChunHong Pan
2014 Science China Information Sciences  
In this work, a new particle filter based visual tracking algorithm is proposed.  ...  By introducing a new cooperative fusion strategy, the proposed tracker has better fault tolerance ability than the traditional methods.  ...  Cooperative fusion particle filter tracker Particle filter Denote the target state and observation at discrete time t by x t and z t , respectively.  ... 
doi:10.1007/s11432-013-4853-2 fatcat:nhdbry3gmracfauvhvgzt64sja

On-line spam filter fusion

Thomas R. Lynam, Gordon V. Cormack, David R. Cheriton
2006 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '06  
These tests supported the primary hypothesis -that naïve fusion improves on the best base filter.  ...  The principal objective of these tests was to test the primary hypothesis; a secondary objective was to examine the effectiveness of new fusion and subset selection methods.  ...  The 53 filters tested at TREC include many of the best available filters at the time of writing, as well as several experimental and less-well-performing filters.  ... 
doi:10.1145/1148170.1148195 dblp:conf/sigir/LynamCC06 fatcat:6jdx7vvedjephpydyt4oza6jym

Distributed Kalman Filtering [chapter]

2014 Networked Filtering and Fusion in Wireless Sensor Networks  
The most well-known and widely used probabilistic estimation methods are the Kalman filter and its extension to nonlinear systems, the Extended Kalman Filter (Kalman, 1960; Welch and Bishop, 2002) .  ...  The filter supports the estimation of past, present and future states, even if a precise model of the system considered is unknown.  ...  has been the subject of extensive research and applications, particularly in the area of autonomous robots, assisted navigation and sensor data fusion (Lee et al., 1995; Dorfmüller-Ulhaas, 2003; Caron  ... 
doi:10.1201/b17667-5 fatcat:m7zdr62rpjforc7l546jfhiyla

Sensor Data Fusion Using Kalman Filter

Athira Chandra Babu, Ravi Kumar Karri, Nisha M S
2018 2018 International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C)  
This paper presents the data fusion system for mobile robot navigation. Odometry and sonar signals are fused using Extended Kalman Filter (EKF) and Adaptive Fuzzy Logic System (AFLS).  ...  The AFLS was used to adapt the gain and therefore prevent the Kalman filter divergence. The fused signal is more accurate than any of the original signals considered separately.  ...  If this is happened, the Kalman filter would diverge or at best converge to a large bound. Jetto et. al. [7] used fuzzy logic adapted Kalman filter to prevent the filter from divergence.  ... 
doi:10.1109/icdi3c.2018.00015 fatcat:c323vzkxyvbdpjo45d4lwelbfm

Globally optimal distributed Kalman filtering fusion

XiaoJing Shen, YingTing Luo, YunMin Zhu, EnBin Song
2012 Science China Information Sciences  
The global optimality in this paper means that the distributed Kalman filtering fusion is exactly equal to the corresponding centralized optimal Kalman filtering fusion.  ...  distributed Kalman filtering fusion are not completely satisfied.  ...  Optimal distributed random Kalman filtering fusion Ref.  ... 
doi:10.1007/s11432-011-4538-7 fatcat:3kd5q3fwdzc3zcwt6j326ei7ti

Multiscale image fusion through guided filtering

Alexander Toet, Maarten A. Hogervorst, Karin U. Stein, Ric H. M. A. Schleijpen
2016 Target and Background Signatures II  
We introduce a multiscale image fusion scheme based on guided filtering. Guided filtering can effectively reduce noise while preserving detail boundaries.  ...  The proposed multi-scale image fusion scheme achieves optimal spatial consistency by using guided filtering both at the decomposition and at the recombination stage of the multiscale fusion process.  ...  Section 2 briefly discusses the principles of edge preserving filtering and introduces (iterative) guided filtering. Section 3 presents the proposed guided fusion based image fusion scheme.  ... 
doi:10.1117/12.2239945 fatcat:75rrvmu3jfh6batz4iwohnrxkm

Sensor data fusion using Kalman filter

J.Z. Sasiadek, P. Hartana
2000 Proceedings of the Third International Conference on Information Fusion  
This paper presents the data fusion system for mobile robot navigation. Odometry and sonar signals are fused using Extended Kalman Filter (EKF) and Adaptive Fuzzy Logic System (AFLS).  ...  The AFLS was used to adapt the gain and therefore prevent the Kalman filter divergence. The fused signal is more accurate than any of the original signals considered separately.  ...  If this is happened, the Kalman filter would diverge or at best converge to a large bound. Jetto et. al. [7] used fuzzy logic adapted Kalman filter to prevent the filter from divergence.  ... 
doi:10.1109/ific.2000.859866 fatcat:v3eafdmgd5dv7nj4k7mm4wiyzi

Multimodal Sensor Fusion with Differentiable Filters [article]

Michelle A. Lee, Brent Yi, Roberto Martín-Martín, Silvio Savarese, Jeannette Bohg
2020 arXiv   pre-print
Differentiable filters provide a way to learn these models end-to-end while retaining the algorithmic structure of recursive filters.  ...  Leveraging multimodal information with recursive Bayesian filters improves performance and robustness of state estimation, as recursive filters can combine different modalities according to their uncertainties  ...  The multimodal feature is then used as an observation in the recurrent filter architecture. We call our filters Feature Fusion EKF and Feature Fusion PF. B.  ... 
arXiv:2010.13021v2 fatcat:vqjehkkp6nb33oyffxzo72l2xq

Distributed Fusion Kalman Self-Turning Filter

Ming Bo Zhang
2013 Advanced Materials Research  
This paper puts forward an optimal and distributed fusion Kalman filter based on the Riccati equation, optimal and distributed fusion The Kalman filter has fewer calculated dimensions and less calculated  ...  amount than the centralized global optimal Kalman filter.  ...  Then substitute the results into the weighted distributed fusion Kalman filter in order to get the distributed fusion self-turning Kalman filter.  ... 
doi:10.4028/www.scientific.net/amr.760-762.1661 fatcat:bvdcng3otrcjxo37eb2ssmk34m

Consensus-Based Distributed Filtering with Fusion Step Analysis [article]

Jiachen Qian, Peihu Duan, Zhisheng Duan, Guanrong Chen, Ling Shi
2022 arXiv   pre-print
For consensus on measurement-based distributed filtering (CMDF), through infinite consensus fusion operations during each sampling interval, each node in the sensor network can achieve optimal filtering  ...  and that of centralized filtering.  ...  fusion on the steady-state performance of the CM-based distributed filtering algorithm. (2) Based on the above analysis, find out the relationship between fusion step L and performance degradation compared  ... 
arXiv:2112.06395v3 fatcat:ya4vocgvcjczhj4xc2eh3f6rx4

Unification of Fusion Theories, Rules, Filters, Image Fusion and Target Tracking Methods (UFT) [article]

Florentin Smarandache
2015 arXiv   pre-print
, image fusion procedures, filter algorithms, and target tracking methods for more accurate applications to our real world problems - since neither fusion theory nor fusion rule fully satisfy all needed  ...  For each particular application, one selects the most appropriate fusion space and fusion model, then the fusion rules, and the algorithms of implementation.  ...  Unification of Fusion Theories, Rules, Filters, Image Fusion and Target Tracking Methods (UFT) 9 5. F.  ... 
arXiv:1507.07462v1 fatcat:dicj6qg6lzabpoqyqt2iuebck4
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