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Image stabilization (IS) is a family of techniques that reduce blurring associated with the motion of a camera or other imaging device during exposure.. Generally, it compensates for pan and tilt (angular movement, equivalent to yaw and pitch) of the imaging device, though electronic image stabilization can also compensate for rotation about the optical axis (). [1]
Digital image correlation and tracking is an optical method that employs tracking and image registration techniques for accurate 2D and 3D measurements of changes in images. This method is often used to measure full-field displacement and strains , and it is widely applied in many areas of science and engineering.
Digital image authentication is an issue [34] for the providers and producers of digital images such as health care organizations, law enforcement agencies, and insurance companies. There are methods emerging in forensic photography to analyze a digital image and determine if it has been altered.
Image analysis or imagery analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. [1] Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face .
This approach is contrasted to digital image stabilization in which the physical image is allowed to "track" the scene on the CCD by software to produce a stable image. The digital technique requires the pixel count to be increased to allow the image to move on the sensor while keeping reference points within the boundaries of the capture chip.
Image stabilization. Technology to minimize image blurring by camera movement during exposure. See also AS, OS, OIS, OSS, SR, SS, SSI, SSS, VR as brand-specific terms. [10] ISO: A system for quantifying the sensitivity ("speed") of a photographic emulsion, or a solid-state digital-camera's image sensor, to visible light. Normally followed by a ...
A digital image is an image composed of picture elements, also known as pixels, each with finite, discrete quantities of numeric representation for its intensity or gray level that is an output from its two-dimensional functions fed as input by its spatial coordinates denoted with x, y on the x-axis and y-axis, respectively. [1]
Digital image processing allows the use of much more complex algorithms, and hence, can offer both more sophisticated performance at simple tasks, and the implementation of methods which would be impossible by analogue means. In particular, digital image processing is a concrete application of, and a practical technology based on: Classification