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Combined with the gradient similar measure, this paper proposes a new algorithm to register the images based on registration operator. By using the bilinear interpolation to express the relationship between the image to be registered and the reference image, the method transfers the registration problem to parameter estimation. And on the basis of the revised gradient similar measure, we construct...
The descriptive capability of color images for a scene is better than that of grayscale images. Traditional registration methods to register color images convert them to grayscale ones, in which the registration precision is decreased due to the loss of color information. By extending some properties of the discrete Fourier transform to the quaternion domain, a discrete-quaternion-Fourier-transform-based...
This paper presents an efficient method of subpixel image registration based on the phase-only correlations (POCs) of image projections. Conventional POC-based methods need the two-dimensional discrete Fourier transforms three-times for calculating the 2-D POC of images. In order to reduce the computational cost caused by the two-dimensional discrete Fourier transforms, we decompose the two-dimensional...
This paper describes a generic method for vision-based navigation in real urban environments. The proposed approach relies on a representation of the scene based on spherical images augmented with depth information and a spherical saliency map, both constructed in a learning phase. Saliency maps are built by analyzing useful information of points which best condition spherical projections constraints...
This paper presents a method that estimates both the photometric mapping and the dense motion field in image sequences. The method extends the Horn-Schunck type dense variational optical flow estimation approach with the use of intensity mapping functions in an alternating optimization scheme. The intensity mapping functions are also updated through the iterations with the help of weighted histograms,...
This paper presents a novel disparity map refinement method and vision based surveillance framework for the task of detecting objects of interest in dynamic outdoor environments from two stereo video sequences taken at different times and from different viewing angles by a mobile camera platform. The proposed framework includes several steps, the first of which computes disparity maps of the same...
Image registration has traditionally been performed by estimating parametric transformation between two images. In this paper, we extend the standard approach to multiple images and adopt the photogrammetric process to improve accuracy of registration. In particular, we use a multi-head camera mount providing multiple non-overlapping images per time epoch and use multiple epochs which increase the...
In this paper a novel method for registration of multitemporal very high geometrical resolution (VHR) remote sensing images is presented. It relies on the extraction of a large set of control points (CPs) used for the estimation of a disparity map exploited for the registration process. CPs are automatically identified in both the images through the estimation and analysis of the distribution of registration...
A method is proposed to process registered images to reduce the effects of registration noise in change detection. The proposed method is based on the pixel-level misregistration map and the gradients of the registered image. Thin plate spline (TPS) transform is selected to estimate the misregistration of each pixel using available tie points. For each pixel, the compensation is composed of two parts:...
In this paper, we present a new approach that combines quaternion Fourier transform and parametric template method for registering color images that allows for scaling, translation, and rotation. We can accurately estimate model geometrical parameters based on the properties of quaternion Fourier transform. Inspired by parametric template method that allows fast estimation of the model parameters...
We propose a structural image representation and show its relevance for multi-modal image registration. Structural representation means that only the structures in the image matter and not the intensity values of their depiction. The representation is formulated as a dense descriptor. We specify three properties an optimal descriptor for structural registration has to fulfill: locality preservation,...
Image super-resolution is a technique of combining a set of overlapping low-resolution (LR) images to produce a high-resolution (HR) image. This technique has two main steps; the first step is alignment of LR images that should be done with sub-pixel accuracy and the second step is the reconstruction stage. In this paper, we improve the works done beforehand in image registration. The planar motion...
In this paper, we present a new rotation estimation and recovery algorithm. The algorithm recovers the rotated images with high quality through minimizing the number of pixels whose intensities need to be altered. The recovery algorithm can tolerate up to about +/-4 degrees error in the estimation of the angle of rotation. To estimate the angle of rotation, a non-rotated version of the rotated image...
In this paper, we propose a robust estimation method to coregistration error for synthetic aperture radar interferometry (InSAR) interferometric phase. In the method, the optimal joint data vector is determined, the true steering vector is computed according to the data vector, and then the beamforming technique with the steering vector is used to estimate the InSAR interferometric phase. The method...
Registration between 3-D volumes and 2-D fluoro images for Electrophysiology (EP) is a challenging task due to the lack of corresponding features between 2-D and 3-D data. This paper presents an automatic, accurate and workflow-friendly 2-D/3-D registration method specially designed for patient movement correction during EP procedures. Firstly, 2-D spines are enhanced by exploiting the temporal information...
Compensating for cardio-thoracic motion artifacts in contrast-enhanced cardiac perfusion MRI (p-MRI) sequences is a key issue for the quantitative assessment of myocardial iscæmia. The classical paradigm consists of registering each sequence frame on some reference using an intensity-based matching criterion. In this paper, we present a novel unsupervised method for the groupwise registration of cardiac...
The majority of image registration methods deal with registering only two images at a time. Recently, a clustering method that concurrently registers more than two multi-sensor images was proposed, dubbed ensemble clustering. In this paper, we apply the ensemble clustering method to a deformable registration scenario for the first time. Non-rigid deformation is implemented by a free-form deformation...
Now-a-days image alignment is one of the most widely used techniques in computer vision. Image alignment has many applications in fields as diverse as video surveillance, computer vision, medical imaging, and video coding. The estimation of an objects' motion is a key step in image alignment. In this paper, we will present a low-complexity algorithm for estimation of motion parameters. Most of the...
This paper proposes a new image registration method using no reference image. The proposed method embeds a two dimensional tracking pattern to the Fourier magnitude domain of an image to generate a stego image, by data hiding scheme based on a log-polar mapping. Once a stego image is geometrically deformed, this method estimates rotation angle and resizing scale by correlation between the original...
This paper proposes an image registration method in which a geometrical deformed image is geometrically compensated without using its corresponding reference image. The proposed method hides a simple two-dimensional matrix into an original image in the spatial domain to generate a stego image. Once a stego image is geometrically deformed, this method estimates the geometric parameters by correlation...
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