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Image stitching is widely used in modern applications, such as the following: Document mosaicing [5] Image stabilization feature in camcorders that use frame-rate image alignment; High-resolution image mosaics in digital maps and satellite imagery; Medical imaging; Multiple-image super-resolution imaging; Video stitching [6] Object insertion
Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. SIFT keypoints of objects are first extracted from a set of reference images [1] and stored in a database.
combine overlapping images for panoramic photography; correct complete panorama images, e.g. those that are "wavy" due to a badly levelled panoramic camera; stitch large mosaics of images and photos, e.g. of long walls or large microscopy samples; find control points and optimize parameters with the help of software assistants/wizards
where (,) is the predicted projection of point on image and (,) denotes the Euclidean distance between the image points represented by vectors and . Because the minimum is computed over many points and many images, bundle adjustment is by definition tolerant to missing image projections, and if the distance metric is chosen reasonably (e.g ...
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
[1] [2] The software uses SIFT and RANSAC. It differs from some other image-stitching software in that it automatically and seamlessly stitches together even unaligned or zoomed photographs without user input, whereas others often require the user to highlight matching areas for the photographs to be merged properly. The only requirement is ...
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Texture synthesis is the process of algorithmically constructing a large digital image from a small digital sample image by taking advantage of its structural content. It is an object of research in computer graphics and is used in many fields, amongst others digital image editing, 3D computer graphics and post-production of films.