Super resolution (SR) methods strive to generate a high resolution (HR) image utilizing several low resolution (LR) images taken from different views. Although this procedure is worthwhile in astronomical imagery, most of methods – including Harris feature point extraction – are not appropriate for registering astronomical images. In this work, we propose a simple, fast and accurate registratio...

In this paper, we present feature-based technique for construction of mosaic image from underwater video sequence, which suffers from parallax distortion due to propagation properties of light in the underwater environment. The most of the available mosaic tools and underwater image mosaicing techniques yields final result with some artifacts such as blurring, ghosting and seam due to presence ...

This paper presents a procedure for the automatic registration of thermographies with laser scanning point clouds. Given the heterogeneous nature of the two modalities, we propose a feature-based approach, satisfying the requisite that extracted features have to be invariant not only to rotation, translation and scale but also to changes in illumination and dimensionality. As speed and minimum ...

The faithful 3D reconstruction of urban environments is an important prerequisite for tasks such as city modeling, scene interpretation or urban accessibility analysis. Typically, a dense and accurate 3D reconstruction is acquired with terrestrial laser scanning (TLS) systems by capturing several scans from different locations, and the respective point clouds have to be aligned correctly in a c...

This paper studies the iris recognition problem in the degraded iris images captured in non-ideal imaging conditions. In these circumstances iris recognition becomes challenging because of noisy factors such as the off-axis imaging, pose variation, image blurring, illumination change, occlusion, specular highlights and noise. We introduce a robust algorithm based on the Random Sample Consensus ...

Scans acquired by 3D sensors are typically represented in a local coordinate system. When multiple scans, taken from different locations, represent the same scene these must be registered to a common reference frame. We propose a fast and robust registration approach to automatically align two scans by finding two sets of N -points, that are approximately congruent under rigid transformation an...

In this paper, a convolutional neural network-based registration framework is proposed for remote sensing to improve the accuracy between two remote-sensed images acquired from different times and viewpoints. The consists of four stages. first stage, key-points are extracted input images—a reference sensed image. Then, patch constructed at each key-point. second stage three processes matching—c...

One of the attractive properties of RANSAC [2], at least with the tophat (inlier 1, outlier 0) cost function, is that it returns an optimal solution with a predefined, user-controllable probability. The theoretical guarantee is based on the assumption that all all-inlier (minimal) samples lead to the optimal solution. It has been observed [1, 9] that the assumption is not valid in practice and ...

Many feature tracking algorithms have been proposed for motion segmentation, but the resulting trajectories are not necessarily correct. In this paper, we propose a technique for removing outliers based on the knowledge that correct trajectories are constrained to be in a subspace of their domain. We first fit an appropriate subspace to the detected trajectories using RANSAC and then remove out...