A synthesis of an optimal fuzzy filter based on local statistics

1995 ◽  
Vol 78 (8) ◽  
pp. 10-21 ◽  
Author(s):  
Hironori Takashima ◽  
Akin Taguchi ◽  
Yutaka Murata
Keyword(s):  
Fuzzy Filter ◽  
Local Statistics

Switching based fuzzy filter for salt-and-pepper noise

2013 ◽  
Vol 32 (5) ◽  
pp. 1293-1295
Author(s):  
Yuan-hua GUO ◽  
Xiao-rong HOU
Keyword(s):  
Salt And Pepper Noise ◽  
Fuzzy Filter ◽  
Salt And Pepper

Directional weighted hybrid median based fuzzy filter for de-noising random valued impulse noise

2020 ◽  
Author(s):  
R. Marudhachalam ◽  
S. Selvanayaki ◽  
R. Tamilselvi ◽  
P. Devaki
Keyword(s):  
Impulse Noise ◽  
Fuzzy Filter

scholarly journals Consistency of bootstrap approximation to the null distributions of local spatial statistics with application to house price analysis

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Chang-Lin Mei ◽  
Shou-Fang Xu ◽  
Feng Chen
Keyword(s):  
Spatial Statistics ◽  
Bootstrap Method ◽  
Spatial Association ◽  
House Price ◽  
Housing Price ◽  
Bootstrap Approximation ◽  
Local Statistics ◽  
Null Distributions ◽  
Local Spatial Statistics ◽  
Distribution Of A Statistic

Abstract With the increasing availability of spatially extensive geo-referenced data, much attention has been paid to the use of local statistics to identify local patterns of spatial association, in which the null distributions of local statistics play an essential role in the related statistical inference. As a powerful tool to approximate the distribution of a statistic, the bootstrap method is used in this paper to derive null distributions of the commonly used local spatial statistics including local Getis and Ord’s $G_{i}$ G i , Moran’s $I_{i}$ I i and Geary’s $c_{i}$ c i . Strong consistency of the bootstrap approximation to the null distributions of the statistics is proved under some mild conditions, and the Boston housing price data are analyzed to demonstrate the application of the theoretical results.

scholarly journals Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4418 ◽  
Author(s):  
Aleksandra Sekrecka ◽  
Michal Kedzierski
Keyword(s):  
High Ratio ◽  
Data Sets ◽  
Spectral Quality ◽  
Local Statistics ◽  
Panchromatic Image ◽  
Urbanized Area ◽  
Fusion Methods ◽  
Spatial Quality ◽  
Different Levels

Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area.

Mass detection on real and synthetic mammograms: human observer templates and local statistics

2007 ◽  
Author(s):  
Cyril Castella ◽  
Karen Kinkel ◽  
Francis R. Verdun ◽  
Miguel P. Eckstein ◽  
Craig K. Abbey ◽  
...  
Keyword(s):  
Human Observer ◽  
Mass Detection ◽  
Local Statistics

scholarly journals Generalizations of(∈,∈∨q)-Fuzzy Filters inR0-Algebras

2010 ◽  
Vol 2010 ◽  
pp. 1-19
Author(s):  
Young Bae Jun ◽  
Seok Zun Song ◽  
Jianming Zhan
Keyword(s):  
Fuzzy Filter ◽  
Fuzzy Filters

Generalizations of a part of the paper (Ma et al., 2009) are considered. As a generalization of an(∈,∈∨q)-fuzzy filter, the notion of an(∈,∈∨qk)-fuzzy filter is introduced, and its characterizations are provided. The implication-based fuzzy filters of anR0-algebra are discussed.

A fuzzy filter for the removal of random impulse noise in image sequences

2011 ◽  
Vol 29 (6) ◽  
pp. 407-419 ◽  
Author(s):  
Tom Mélange ◽  
Mike Nachtegael ◽  
Stefan Schulte ◽  
Etienne E. Kerre
Keyword(s):  
Impulse Noise ◽  
Image Sequences ◽  
Fuzzy Filter ◽  
Random Impulse
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