cpcorr

Tune control point locations using cross-correlation

Syntax

movingPointsAdjusted = cpcorr(movingPoints,fixedPoints,moving,fixed)

Description

movingPointsAdjusted = cpcorr(movingPoints,fixedPoints,moving,fixed) adjusts the position of moving control points, movingPoints, with respect to fixed control points, fixedPoints, using normalized cross-correlation between the moving image moving and the fixed image fixed. The cpcorr function returns the adjusted moving control points in movingPointsAdjusted.

Examples

Fine-Tune Control-Point Locations using Cross Correlation

Read two images into the workspace.

moving = imread('onion.png');
fixed = imread('peppers.png');

Define sets of control points for both images.

movingPoints = [118 42;99 87];
fixedPoints = [190 114;171 165];

Display the images, and display the control points in white. The position of the moving points is slightly offset from the position of the fixed points.

imshow(fixed)
hold on
plot(fixedPoints(:,1),fixedPoints(:,2),'xw') 
title('Fixed Image')

figure
imshow(moving)
hold on
plot(movingPoints(:,1),movingPoints(:,2),'xw') 
title('Moving Image')

Adjust the moving control points using cross correlation.

movingPointsAdjusted = cpcorr(movingPoints,fixedPoints, ...
    moving(:,:,1),fixed(:,:,1))

movingPointsAdjusted = 2×2

  115.9000   39.1000
   97.0000   89.9000

Display the adjusted moving points in yellow. Compared to the original moving points (in white), the adjusted points more closely match the positions of the fixed points.

plot(movingPointsAdjusted(:,1),movingPointsAdjusted(:,2),'xy')

Input Arguments

movingPoints — Coordinates of control points in image to be transformed

m-by-2 matrix

Coordinates of control points in the image to be transformed, specified as an m-by-2 matrix. The two columns represent the x- and y-coordinates of the control points, respectively, in the intrinsic coordinate system of the image.

Example: [127 93; 74 59]

Data Types: double

fixedPoints — Coordinates of control points in reference image

p-by-2 matrix

Coordinates of control points in the reference image, specified as an p-by-2 matrix. The two columns represent the x- and y-coordinates of the control points, respectively, in the intrinsic coordinate system of the image.

Example: [323 195; 269 161]

Data Types: double

moving — Image to be registered

numeric array

Image to be registered, specified as a numeric array.

fixed — Reference image in target orientation

numeric array

Reference image in the target orientation, specified as a numeric array.

Output Arguments

movingPointsAdjusted — Adjusted coordinates of control points in the image to be transformed

numeric matrix

Adjusted coordinates of control points in the image to be transformed, returned as a numeric matrix of the same size as movingPoints.

Data Types: double

Tips

• The moving and fixed images must have the same scale for cpcorr to be effective.

• If cpcorr cannot correlate a pair of control points, movingPointsAdjusted contains the same coordinates as movingPoints for that pair.

• cpcorr cannot adjust a point if any of these conditions occur:

  • points are too near the edge of either image

  • regions of images around points contain Inf or NaN

  • region around a point in moving image has zero standard deviation

  • regions of images around points are poorly correlated

Algorithms

cpcorr only moves the position of a control point by up to four pixels. Adjusted coordinates are accurate up to one-tenth of a pixel. cpcorr is designed to get subpixel accuracy from the image content and coarse control point selection.

Extended Capabilities

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

Version History

Introduced before R2006a

R2021b: Support for thread-based environments

cpcorr now supports thread-based environments.