Linear granulometric moments of noisy binary images
Academic Article
Overview
Identity
Additional Document Info
Other
View All
Overview
abstract
The first and second moments of the granulometric pattern spectrum are expressed for a random binary image that is formed either as the union of a deterministic signal with random point noise or as the set subtraction of random point noise from a deterministic signal. The granulometry is generated by a vertical (or horizontal) linear structuring element, and there are no constraints placed on the structure of the uncorrupted signal. Because the noise is random, the image on which the granulometry is run is random. Hence the pattern spectrum is a random function with random-variable moments. For both the union and subtractive cases, expressions are found for the expectation of the pattern-spectrum mean and variance, where the expectation is relative to the noise intensity. In each case a recursive formula is obtained for the key expression. 1993 Kluwer Academic Publishers.
