Aerial Images Rectification Using Non-parametric Approach
Geometric distortions caused by different sources usually are accumulated and not present singly in a remotely sensed image. In addition, the effects of geometric distortions are found unequally in the entire image. Hence, aerial images should be rectified before proceed with subsequent images anal...
محفوظ في:
المؤلفون الرئيسيون: | , , , |
---|---|
التنسيق: | E-Article |
اللغة: | English |
منشور في: |
Journal of Convergence
2013
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://ir.unimas.my/id/eprint/5187/1/aerial%20images%20rectification%20using%20non%20-parametic%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/5187/ http://ir.unimas.my/5187/1/aerial%20images%20rectification%20using%20non%20-parametic%20%28abstract%29.pdf |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
الملخص: | Geometric distortions caused by different sources usually are accumulated and not present singly in a remotely
sensed image. In addition, the effects of geometric distortions are found unequally in the entire image. Hence, aerial images should be rectified before proceed with subsequent images analysis. Control points and geometric transformation are the essential components in non-parametric approach. Barrel and perspective distortions are usually found in aerial images. This paper studies the deformation rate contributed by control points at different regions in an image before rectification according to different distribution patterns. Besides, this paper also discusses the
appropriate geometric transformation through the concern of the expected distortions. Experiments are conducted using grid images and aerial images to investigate the effect of distributions of control points and the efficiency of global and local geometric transformations for aerial images rectification. It demonstrated
that control points at different image regions have different deformation rates, control points distributed at image centre are less distorted and local transformation performs better in rectifying images with complex distortions. |
---|