DocumentCode
9262
Title
Ranks for Pairs of Spatial Fields via Metric Based on Grayscale Morphological Distances
Author
Daya Sagar, B.S. ; Sin Liang Lim
Author_Institution
Syst. Sci. & Inf. Unit, Indian Stat. Inst., Bangalore, India
Volume
24
Issue
3
fYear
2015
fDate
Mar-15
Firstpage
908
Lastpage
918
Abstract
Based on a set of morphological distances computed between the grayscale images (spatial fields) of similar size specifications, the ratios of selected morphological distances, and the ratios of areas of infima and suprema of grayscale images, a new metric to quantify the degree of similarity between the grayscale images is proposed. We denote the two spatial fields (grayscale images), respectively, with fi and fj, and the infima and suprema of these spatial fields with (fi ∧ fj) and (fi ⋁ fj). The three morphology-based distances include: 1) dilation distance d( fi, fj); 2) erosion distance e(fi, fj); and 3) median-based distance MN(fi, fj). By employing these parameters, which play vital role in construction of parameter-specific interaction matrices, we provide a metric to designate every possible pair of images that can be considered out of a database consisting of a huge number of images. We demonstrate the whole approach on: 1) synthetic spatial fields; 2) a set of 12 similar-sized grayscale images representing cloud-top temperatures of a specific region for 12 different time instants; and 3) four spatial elevation fields to rank possible pairs of images.
Keywords
image classification; image matching; matrix algebra; cloud-top temperature; dilation distance; erosion distance; grayscale images; grayscale morphological distance; image infima; image size specification; image suprema; median-based distance; parameter-specific interaction matrices; similarity degree; spatial field; Equations; Gray-scale; Indexes; Measurement; Shape; Silicon compounds; Spatial databases; Dilation; Erosion; GISci; erosion; mathematical morphology; morphological distances; spatial fields; spatial interaction;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2015.2390135
Filename
7004829
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