Image Alignment/Registration
Image Fusion Systems Research   

Analysis of two or more images of a scene often requires spatial alignment or registration of the images to bring the
images under the same coordinate system. This is required when creating a mosaic from two or more overlapping
images, finding scene changes in multi-temporal images, combining information in multi-modality images, and
separating moving objects from the background in a video obtained by a moving platform. Following are example
applications of image registration.

Image mosaicking: By aligning two or more images of a scene at their overlap areas, a larger image is created
covering areas in both images. An image mosaicking example is give below. Image (c) is obtained by registering and
combining intensities in images (a) and (b).



































Change detection: By aligning images of a scene taken at different times, it becomes possible to compare and
find changes occurred in the scene over time. This capability can be used to compare before and after disaster
images and assess damages caused by the disaster. Frames (a) and (b) below show a segment of the New Jersey
shore before and after the hurricane Sandy. These images are courtesy of NOAA. Frame (c) shows alignment of
images (a) and (b). Image (a) is shown in light blue while image (b) is shown in red. Red and light blue regions
highlight differences in the images and identify areas in the scene that have changed due to the hurricane.







































Image fusion: By aligning multi-modality images, different properties of the underlying scene can be combined into
a single image that contains more information than any of the individual images. An example is given below.
Registration and fusion of (a) an optical image and (b) a thermal image is shown in (c), which now contains both optical
and thermal information. Images (a) and (b) are courtesy of USGS.




































Motion detection: When images are captured by a moving platform, image motion can be due to camera motion,
object motion, or both. To separate object morion from camera motion, images are aligned at the background. Since
background is static, once video frames are aligned at the background, moving objects in the scene can be detected.
Images (a) and (b) below show two video frames taken moments apart by a moving camera. Registration of the images
is shown in image (c). The green and blue bands in image (c) are the same as the green and blue bands in image (a),
and the red band in image (c) is the same as the red band in image (b) after it is aligned with image (a). The combined
image shows the static background in its natural color, while moving objects (cars and tree branches) as red or light
blue regions. The light blue cars in the bottom-left part of image (c) show cars in motion.
(a)                                                                                   (b)
(c)
(a)                                                                           (b)
(c)
(a)                                                                                 (b)
(c)
(a)                                                                                 (b)
(c)
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Some of the capabilities of this software are:
  1. Automatic and interactive alignment: The images can be interactively or automatically aligned.
  2. Rigid and nonrigid alignment: The software is capable of aligning images with and without local
    geometric differences.
  3. Robust alignment: The software is capable of aligning images at the presence of noise and occlusion.
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