Compensating directional filtering method in the spatial domain and its applications

2018 ◽  
Author(s):  
Yunxiang Liu
Keyword(s):  
Spatial Domain ◽  
Filtering Method ◽  
Directional Filtering

Paper Filtering Method Using Features of Co-Author Research Group, Subject Category and Terminology

2008 ◽  
Vol 128 (8) ◽  
pp. 1358-1366 ◽  
Author(s):  
Masao Yamamoto ◽  
Hisao Mase ◽  
Hiroshi Yajima ◽  
Hiroshi Kinukawa
Keyword(s):  
Research Group ◽  
Filtering Method ◽  
Subject Category

APLIKASI PENAJAMAN CITRAA STREET VIEW MENGGUNAKAN METODE GRAMD SCHMIDT SPECTRAL SHARPENING DAN HIGH PASS FILTERING

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Erna Verawati ◽  
Surya Darma Nasution ◽  
Imam Saputra
Keyword(s):  
Image Processing ◽  
Visual Information ◽  
Intensity Difference ◽  
Original Image ◽  
Filtering Method ◽  
The Road ◽  
Street View ◽  
Result Show ◽  
Filter Process ◽  
High Pass

Sharpening the image of the road display requies a degree of brightness in the process of sharpening the image from the original image result of the improved image. One of the sharpening of the street view image is image processing. Image processing is one of the multimedia components that plays an important role as a form of visual information. There are many image processing methods that are used in sharpening the image of street views, one of them is the gram schmidt spectral sharpening method and high pass filtering. Gram schmidt spectral sharpening method is method that has another name for intensity modulation based on a refinement fillter. While the high pass filtering method is a filter process that btakes image with high intensity gradients and low intensity difference that will be reduced or discarded. Researce result show that the gram schmidt spectral sharpening method and high pass filtering can be implemented properly so that the sharpening of the street view image can be guaranteed sharpening by making changes frome the original image to the image using the gram schmidt spectral sharpening method and high pass filtering.Keywords: Image processing, gram schmidt spectral sharpening and high pass filtering.

Aspect and space

2017 ◽  
Author(s):  
Lucas Champollion
Keyword(s):  
Spatial Domain ◽  
The Other ◽  
Alternative View ◽  
Temporal Domain ◽  
Spatial Aspect ◽  
Temporal Aspect ◽  
The Way

This chapter models the relation between temporal aspect (run for an hour vs. *run all the way to the store for an hour) and spatial aspect (meander for a mile vs. *end for a mile) previously discussed by Gawron (2009). The chapter shows that for-adverbials impose analogous conditions on the spatial domain and on the temporal domain, and that an event may satisfy stratified reference with respect to one of the domains without satisfying it with respect to the other one as well. This provides the means to extend the telic-atelic opposition to the spatial domain. The chapter argues in some detail that stratified reference is in this respect empirically superior to an alternative view of telicity based on divisive reference (Krifka 1998).

scholarly journals QuickBird image-based estimation of tree stand density using local maxima filtering method: A case study in a Beijing forest

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0208256
Author(s):  
Shuhan Wang ◽  
Xiaoli Zhang ◽  
Mohammed Abdelmanan Hassan ◽  
Qi Chen ◽  
Chaokui Li ◽  
...  
Keyword(s):  
Stand Density ◽  
Tree Stand ◽  
Local Maxima ◽  
Filtering Method
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