L. M. G. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Engineering and Remote Sensing, 62(9):1049--1056, Sept. 1996. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Multisensor Image Registration By Feature Consensus - Shekhar, Govindu, Chellappa (1996) (3 citations) (Correct)
....prostheses, metallic probes etc. in medical imagery also give rise to features that are likely to be preserved in multisensor images. Feature based methods that exploit the information contained in region boundaries and in man made structures are therefore useful for multisensor registration [4, 5, 10, 11]. Feature based methods traditionally rely on establishing feature correspondence between the two images. Such correspondence based methods first employ feature matching techniques to determine corresponding feature pairs from the two images, and then compute the geometric transformation relating ....
L. Fonseca and B. S. Manjunath, "Registration techniques for multisensor remotely-sensed imagery," Photogrammetric Engineering and Remote Sensing, Sept. 1996. In press.
Change Detection in Overhead Imagery using Neural Networks - Clifton (2003) (1 citation) (Correct)
....presented here is the need for image registration. To build a vector for a location, that location must be identified on all of the images. This will generally require warping the images to a common standard orthorectification. Although techniques for automatic image registration are known [FM96, SD96, DKC96] it is nontrivial to achieve pixel level matching (although this is improving, see [CSR99] However, as discussed in the preceding paragraph and shown in the example in Section 5.2, pixel level resolution is not usually necessary. Therefore registration is only needed to within a ....
L. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Engineering and Remote Sensing, 62(9), 1996.
Combined Invariants To Linear Filtering And Rotation - Flusser, Zitova (1999) (2 citations) (Correct)
....registration, that eliminates the impact of imaging geometry and transforms the image into some standard form, and blind deconvolution, that removes or suppresses the blurring. Both these steps have been extensively studied in the literature, we refer to the recent surveys on registration [4] [7] and on deconvolution restoration techniques [10] 16] 1 Generally, image normalization is an ill posed problem whose computing complexity can be extremely high. In the invariant approach we look for image descriptors (features) that do not depend on h(x; y) x; y) and a. In this way we avoid ....
L. M. G. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Eng. Remote Sensing, 62:1049--1056, 1996.
Automatic Registration of Satellite Images - Leila Fonseca Max (1998) Self-citation (Fonseca) (Correct)
No context found.
L. M. G. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Engineering and Remote Sensing, 62(9):1049--1056, Sept. 1996.
Automatic Registration of Satellite Images - Fonseca, Costa (1997) Self-citation (Fonseca) (Correct)
No context found.
L. M. G. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Engineering and Remote Sensing, 62(9):1049--1056, Sept. 1996.
Automatic Registration of Satellite Images - Fonseca, Costa (1997) Self-citation (Fonseca) (Correct)
....is the process of matching two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged. It is a classical problem in several image processing applications where it is necessary to match two or more images of the same scene [8].The registration process is usually carried out in three steps. The first step consists of selection of features on the images. Next each feature in one image is compared with potential corresponding features in the other image. A pair of features with similar attributes are accepted as matches ....
L. M. G. Fonseca and B. S. Manjunath. Registration techniques for multisensor remotely sensed imagery. Photogrammetric Engineering and Remote Sensing, 62(9):1049--1056, Sept. 1996.
Object-Based Representations Of Spatial Images - Newsam, Bhagavathy, Kenney.. (2001) Self-citation (Fonseca Manjunath) (Correct)
....has traditionally been the aquisition of control points. In remote sensing applications, users generally use manual registration which is not feasible in cases where there is a large amount of data. Thus, there is a need for automated techniques that require little or no operator supervision [10]. The most difficult registration cases are: 1) images from different sensors; 2) images taken at different times or under different conditions; and (3) radar images. Speckle noise in radar images can produce artifacts that mimic good control points and lead to low precision or even wrong ....
Fonseca, L.M.G. and Manjunath, B.S, "Registration Techniques for Multisensor Remotely Sensed Imagery," Photogrammetric Engineering and Remote Sensing, v. 62, n. 9, pp. 1049-1056, Sept. 1996.
Multi-Image Registration for an Enhanced Vision System - Hines, Rahman, Jobson.. (2003) (1 citation) (Correct)
No context found.
L. Fonseca and B. Manjunath, "Registration techniques for multisensor remotely sensed imagery," in Photogrammetric Engineering and Remote Sensing, 62, No. 9, pp. 1046--1056, September 1996.
Algorithms Using Inter-band Cross-correlation for Pixel.. - Theiler, Henderson.. (1997) (Correct)
No context found.
L. M. G. Fonesca and B. S. Manjunath, "Registration techniques for multisensor remotely sensed imagery," Photogrammetric Engineering and Remote Sensing 62, pp. 1049--1056, 1996.
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