Howtosignalprocessing
- What is meant by cross-correlation?
- What is the formula for cross-correlation?
- What is the difference between cross-correlation and Pearson correlation?
- What is cross-correlation in image processing?
What is meant by cross-correlation?
Cross-correlation is used to evaluate the similarity between the spectra of two different systems, for example, a sample spectrum and a reference spectrum. This technique can be used for samples where background fluctuations exceed the spectral differences caused by changes in composition.
What is the formula for cross-correlation?
Cross-correlation between Xi and Xj is defined by the ratio of covariance to root-mean variance, ρ i , j = γ i , j σ i 2 σ j 2 . γ ^ i , j = 1 N ∑ t = 1 N [ ( X i t − X ¯ i ) ( X j t − X ¯ j ) ] .
What is the difference between cross-correlation and Pearson correlation?
In the realm of statistics, cross-correlation functions provide a measure of association between signals. The Pearson product-moment correlation coefficient is simply a normalized version of a cross-correlation. When two times series data sets are cross-correlated, a measure of temporal similarity is achieved.
What is cross-correlation in image processing?
Cross-Correlation:
Correlation is the process of moving a filter mask often referred to as kernel over the image and computing the sum of products at each location. Correlation is the function of displacement of the filter.
