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In image processing, the input is an image and the output is an image as well, whereas in computer vision, an image or a video is taken as an input and the output could be an enhanced image, an understanding of the content of an image or even behavior of a computer system based on such understanding.
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. [1] It is used in computer vision, medical imaging, [2] military automatic target recognition, and compiling and analyzing images and data from ...
Digital image processing is the use of a digital computer to process digital images through an algorithm. [1] [2] As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
Computational imaging systems span a broad range of applications. While applications such as SAR, computed tomography, seismic inversion are well known, they have undergone significant improvements (faster, higher-resolution, lower dose exposures [3]) driven by advances in signal and image processing algorithms (including compressed sensing techniques), and faster computing platforms.
2D digital image acquisition is the information source of 3D reconstruction. Commonly used 3D reconstruction is based on two or more images, although it may employ only one image in some cases. There are various types of methods for image acquisition that depends on the occasions and purposes of the specific application.
Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, image registration, video tracking, image mosaicing, panorama stitching, 3D reconstruction and object recognition.
General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).
In computer vision, the Kanade–Lucas–Tomasi (KLT) feature tracker is an approach to feature extraction. It is proposed mainly for the purpose of dealing with the problem that traditional image registration techniques are generally costly. KLT makes use of spatial intensity information to direct the search for the position that yields the ...