Image Registration - Algorithm Classification - Similarity Measures For Image Registration

Similarity Measures For Image Registration

Image similarities are broadly used in medical imaging. An image similarity measure quantifies the degree of similarity between intensity patterns in two images. The choice of an image similarity measure depends on the modality of the images to be registered. Common examples of image similarity measures include cross-correlation, mutual information, sum of squared intensity differences, and ratio image uniformity. Mutual information and normalized mutual information are the most popular image similarity measures for registration of multimodality images. Cross-correlation, sum of squared intensity differences and ratio image uniformity are commonly used for registration of images in the same modality.

Read more about this topic:  Image Registration, Algorithm Classification

Famous quotes containing the words similarity, measures and/or image:

    “Incompatibility. In matrimony a similarity of tastes, particularly the taste for domination.”
    —Ambrose Bierce (1842–1914)

    “They who have been bred in the school of politics fail now and always to face the facts. Their measures are half measures and makeshifts merely. They put off the day of settlement, and meanwhile the debt accumulates.”
    —Henry David Thoreau (1817–1862)

    “The “female culture” has shifted more rapidly than the “male culture”; the image of the go-get ‘em woman has yet to be fully matched by the image of the let’s take-care-of-the-kids- together man. More important, over the last thirty years, men’s underlying feelings about taking responsibility at home have changed much less than women’s feelings have changed about forging some kind of identity at work.”
    —Arlie Hochschild (20th century)