Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal 3D structure and viewing parameter (camera pose and/or calibration) estimates. In order to solve this problem, the algorithm of bundle adjustment is used. After the matching, the not overlapped region has reprojection errors. The fourth stage is the warping or stitching phase, where the images are overlapped to stitch together as one. The goal is to determine a set of inliers from the presented correspondences so that the homography can be estimated optimally from these inliers. RANSAC uses the smallest data set possible and proceeds to enlarge this set with consistent data points. For feature-based methods, the most used techniques are DLT and RANSAC for their performance and robustness. In practice, robust statistical techniques are employed on a large number of matching points or lines after normalizing the data these techniques reduce the adverse effects of noise by using the sum of squared difference method or an iterative mathematical model, such as RANSAC (random sample consensus), PROSAC (progressive sample consensus), or direct linear transformation (DLT), to relate the features and reduce the matching points. Panorama Generationĭifferent techniques are proposed to calculate the homography. Table 1 summarizes the comparisons of the characteristics of satellites and UAVs. However, this work will focus on aerial images obtained through UAVs due to their high resolution, precision, ease, and flexibility. Each system has its own advantages depending on the application. The aforementioned features make them ideal for surveillance and monitoring tasks. Another advantage of UAVs is that they can carry different types of sensors, such as fish-eye cameras, thermographic cameras, LIDAR sensors, and proximity sensors.
In the case of UAVs, aerial image panoramas are mainly based on feature-based methods, due to their flexibility to fly in a specific area, which allows them to focus on the selected region, obtaining images with greater accuracy and sufficient distinctive features. However, there are important factors to evaluate for the use of satellite image acquisition: firstly, if an analysis of a specific section is required, it is necessary to check if any satellite is available for the specific coordinates or has recent information on the area of interest additionally, if the area is small, when zooming to focus on it, the resolution will be lower in comparison to that of a medium-size UAV camera an additional consideration is UAVs’ dependence on the state of the clouds, owing to the fact that satellites are not subjected to weather inclemency, such as storms, as UAVs are for satellite aerial panorama, the methods for mosaicing images are based on cross-correlation, Fourier-based, phase correlation, and area-based approaches. One advantage is that satellite image acquisition is faster than that of UAVs. In aerial panoramas, image acquisition can be performed by satellites or UAV systems, but satellite technology provides a higher coverage area than that of other systems such as UAVs.
#Ghosting on pdf images registration#
Different approaches have been developed for the stitching process, for example, direct methods (pixel-based) and feature-based methods or mosaicing based on registration and mosaicing based on blending. For these applications, aerial mosaic panorama generation is applied to stitch multiple images into a single image based upon overlapped regions. The aerial mosaic has different applications, such as surveillance mapping and tracking, search and rescue, 3D scene reconstruction, inspection in heritage and archeological applications, and vegetation and forest surveillance. For this purpose, a summary of the most applied techniques and their applications is given, showing the trend of the research field and the contribution of different countries over time. This paper aims to show an overview of the most frequently applied mosaicing techniques in UAVs by providing an introduction to those interested in developing in this area.
These methodologies can be categorized into direct methods or feature-based methods. Some applications are photogrammetry and mapping, where the main problems to be solved are image alignment and ghosting images, for which different stitching techniques can be applied. As an example, we can mention the use of aerial photographs for the generation of panoramic images through the process of stitching images without losing image resolution. Such is the case of image processing, in which, by the use of aerial photographs taken by these aircrafts, it is possible to perform surveillance and monitoring tasks. The use of UAV (unmanned aerial vehicle) technology has allowed for advances in the area of robotics in control processes and application development.
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