Estás aquí: start » hiperespectral » hsi-kaze

Alignment of Hyperspectral Images Using KAZE Features

Esta é unha revisión antiga do documento!


Alignment of hyperspectral images using KAZE features

Experimental results related to the paper Alignment of hyperspectral images using KAZE features by Álvaro Ordóñez, Francisco Argüello, and Dora B. Heras, that it is under revision.

Abstract

Image registration is a common operation in any type of image processing, specially in remote sensing images. Since the publication of the scale-invariant feature transform (SIFT) method, several algorithms based on feature detection have been proposed. In particular, KAZE builds the scale space using a nonlinear diffusion filtering instead of Gaussian filters. Nonlinear diffusion filtering allows applying a controlled blur while the important structures of the image are maintained. Hyperspectral images contain a large amount of spatial and spectral information that can be used to perform a more accurate registration. This article presents HSI-KAZE, a method to register hyperspectral remote sensing images based on KAZE but considering the spectral information. The proposed method combines the information of a set of preselected bands, and it adapts the keypoint descriptor and the matching stage to take into account the spectral information. The method is adequate to register images in extreme situations in which the scale between them is very different. The effectiveness of the proposed algorithm has been tested on real images taken on different dates, and presenting different types of changes. The experimental results show that the method is robust achieving image registrations with scales of up to 23.0×.

Downloads

Algorithm

Compiled program to register two hyperspectral images.

  • HSI-KAZE algorithm: coming soon.

Images

All images used in the paper are available in Registration Repository

Example

Example of registration considered in this work: (a) Reference image (size 1096×715), (b) Target image, and © Result of the registration process showing the correctly registered superposition of the reference and target registered image (scale 23.0× and angle of rotation 60º).

License