Robust multi-sensor image alignment
Irani, M.; Anandan, P.
Computer Vision, 1998. Sixth International Conference on
Volume , Issue , 4-7 Jan 1998 Page(s):959 - 966
Digital Object Identifier 10.1109/ICCV.1998.710832
Summary:This paper presents a method for alignment of images acquired by
sensors of different modalities (e.g., EO and IR). The paper has two
main contributions: (i) It identifies an appropriate image
representation, for multi-sensor alignment, i.e., a representation which
emphasizes the common information between the two multi-sensor images,
suppresses the non-common information, and is adequate for
coarse-to-fine processing. (ii) It presents a new alignment technique
which applies global estimation to any choice of a local similarity
measure. In particular, it is shown that when this registration
technique is applied to the chosen image representation with a local
normalized-correlation similarity measure, it provides a new
multi-sensor alignment algorithm which is robust to outliers, and
applies to a wide variety of globally complex brightness transformations
between the two images. Our proposed image representation does not rely
on sparse image features (e.g., edge, contour, or point features). It is
continuous and does not eliminate the detailed variations within local
image regions. Our method naturally extends to coarse-to-fine
processing, and applies even in situations when the multi-sensor signals
are globally characterized by low statistical correlation
View citation and abstract |
Cart
