6533b835fe1ef96bd12a007a
RESEARCH PRODUCT
A robust aerial image registration method using Gaussian mixture models
Yuanyuan WangHamid Reza KarimiChuan Wusubject
Aerial surveyComputer sciencebusiness.industryFeature detectorCognitive NeuroscienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationComputerApplications_COMPUTERSINOTHERSYSTEMSPattern recognitionComputer Science Applications1707 Computer Vision and Pattern RecognitionMixture modelAerial images; Feature detector; Gaussian mixture models; Image registration; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive Neuroscience; Artificial IntelligenceComputer Science ApplicationsComputer Science::RoboticsComputer Science::Systems and ControlArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionAerial imagesComputer visionAerial reconnaissanceArtificial intelligenceGaussian mixture modelsbusinessAerial imageImage registrationdescription
Aerial image registration is one of the bases in many aerospace applications, such as aerial reconnaissance and aerial mapping. In this paper, we propose a novel aerial image registration algorithm which is based on Gaussian mixture models. First of all, considering the characters of the aerial images, the work uses a shape feature detector which computes the boundaries of regions with nearly the same gray-value to extract invariant feature. Then, a Gaussian mixture models (GMM) based image registration model is built and solved to estimate the transformation matrix between two aerial images. Furthermore, the proposed method is applied on real aerial images, and the results demonstrate the improved performance of the proposed algorithm.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-11-01 |