Ranks for Pairs of Spatial Fields via Metric Based on Grayscale Morphological Distances

Daya Sagar, B. S. ; Sin Liang Lim, (2015) Ranks for Pairs of Spatial Fields via Metric Based on Grayscale Morphological Distances IEEE Transactions on Image Processing, 24 (3). pp. 908-918. ISSN 1057-7149

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Official URL: http://doi.org/10.1109/TIP.2015.2390135

Related URL: http://dx.doi.org/10.1109/TIP.2015.2390135

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 f(i) and f(j), and the infima and suprema of these spatial fields with (f(i)∧f(j)) and ( f(i)∨f(j)). The three morphology-based distances include: 1) dilation distance d( f(i),f(j)) ; 2) erosion distance e( f(i),f(j)); and 3) median-based distance MN ( f(i),f(j)) . 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.

Item Type:Article
Source:Copyright of this article belongs to IEEE Society
ID Code:127112
Deposited On:13 Oct 2022 09:02
Last Modified:13 Oct 2022 09:02

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