Registration Estimator
Register 2-D grayscale images
Description
The Registration Estimator app aligns 2-D grayscale images using automatic image registration. Using this app, you can:
Compare feature-based, intensity-based, and nonrigid registration techniques interactively.
Obtain the registered image and the geometric transformation.
Generate a function with the desired registration technique and settings. Call this function to register other images using the same settings.
Feature-Based Techniques
Feature-based registration techniques automatically detect distinct image features such as sharp corners, blobs, or regions of uniform intensity. The moving image undergoes a single global transformation to provide the best alignment of corresponding features with the fixed image.
FAST detects corner features, especially in scenes of human
origin such as streets and indoor rooms. FAST supports single-scale images and
point-tracking.
MinEigen also detects corner features. MinEigen supports
single-scale images and point-tracking.
Harris also detects corner features, using a more efficient
algorithm than MinEigen. Harris supports single-scale images and
point-tracking.
BRISK also detects corner features. Unlike the preceding
algorithms, BRISK supports changes in scale and rotation, and point-tracking.
ORB detects corners in images with changes in scale and/or
rotation.
SURF detects blobs in images and supports changes in scale and
rotation.
KAZE detects multiscale blob features from a scale space
constructed using nonlinear diffusion.
MSER detects regions of uniform intensity. MSER supports
changes in scale and rotation, and is more robust to affine transformations than the
other feature-based algorithms.
Intensity-Based Techniques
Registration Estimator offers three registration techniques that use intensity metric optimization:
Monomodal intensity
Multimodal intensity
Phase correlation
Intensity-based registration techniques correlate image intensity in the spatial or frequency domain. The moving image undergoes a single global transformation to maximize the correlation of its intensity with the intensity of the fixed image.
Monomodal intensity registers images with similar brightness
and contrast that are captured on the same type of scanner or sensor. For example,
use monomodal intensity to register MRI scans taken of similar subjects using the
same imaging sequence.
Multimodal intensity registers images with different brightness
and contrast. These images can come from two different types of devices, such as two
camera models or two types of medical imaging systems (such as CT and MRI). These
images can also come from a single device. For example, use multimodal intensity to
register images taken with the same camera using different exposure settings, or to
register MRI images acquired during a single session using different imaging
sequences.
Phase correlation registers images in the frequency domain.
Like multimodal intensity, phase correlation is invariant to image brightness. Phase
correlation is more robust to noise than the other intensity-based registration
techniques.
Nonrigid Registration Techniques
Nonrigid registration applies nonglobal transformations to the
moving image. Nonrigid transformations generate a displacement field, in which each
pixel location in the fixed image is mapped to a corresponding location in the
moving image. The moving image is then warped according to the displacement field
and resampled using linear interpolation. For more information about estimating a
displacement field for nonrigid transformations, see imregdemons.
Open the Registration Estimator App
MATLAB® Toolstrip: On the Apps tab, under Image Processing and Computer Vision, click the Registration Estimator app icon.
MATLAB command prompt: Enter
registrationEstimator.
Programmatic Use
Tips
You can register images and generate functions for all feature-based techniques without a Computer Vision Toolbox™ license. However, to run an autogenerated function that uses a feature-based registration technique, you must have Computer Vision Toolbox. For more information, see Export Results from Registration Estimator App.
