Image analysisImage analysis or imagery analysis is the extraction of meaningful information from s; mainly from s by means of techniques. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face. Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information.
Super-resolution imagingSuper-resolution imaging (SR) is a class of techniques that enhance (increase) the of an imaging system. In optical SR the diffraction limit of systems is transcended, while in geometrical SR the resolution of digital is enhanced. In some radar and sonar imaging applications (e.g. magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g. MUSIC) and compressed sensing-based algorithms (e.g., SAMV) are employed to achieve SR over standard periodogram algorithm.
Raman scatteringRaman scattering or the Raman effect (ˈrɑːmən) is the inelastic scattering of photons by matter, meaning that there is both an exchange of energy and a change in the light's direction. Typically this effect involves vibrational energy being gained by a molecule as incident photons from a visible laser are shifted to lower energy. This is called normal Stokes Raman scattering. The effect is exploited by chemists and physicists to gain information about materials for a variety of purposes by performing various forms of Raman spectroscopy.
Medical imagingMedical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities.
Back-illuminated sensorA back-illuminated sensor, also known as backside illumination (BI) sensor, is a type of digital that uses a novel arrangement of the imaging elements to increase the amount of light captured and thereby improve low-light performance. The technique was used for some time in specialized roles like low-light security cameras and astronomy sensors, but was complex to build and required further refinement to become widely used. Sony was the first to reduce these problems and their costs sufficiently to introduce a 5-megapixel 1.
Multi-exposure HDR captureIn photography and videography, multi-exposure HDR capture is a technique that creates extended or high dynamic range (HDR) images by taking and combining multiple exposures of the same subject matter at different exposure levels. Combining multiple images in this way results in an image with a greater dynamic range than what would be possible by taking one single image. The technique can also be used to capture video by taking and combining multiple exposures for each frame of the video.
3D computer graphics3D computer graphics, sometimes called CGI, 3D-CGI or three-dimensional , are graphics that use a three-dimensional representation of geometric data (often Cartesian) that is stored in the computer for the purposes of performing calculations and rendering , usually s but sometimes s. The resulting images may be stored for viewing later (possibly as an animation) or displayed in real time. 3D computer graphics, contrary to what the name suggests, are most often displayed on two-dimensional displays.
Bayer filterA Bayer filter mosaic is a color filter array (CFA) for arranging RGB color filters on a square grid of photosensors. Its particular arrangement of color filters is used in most single-chip digital s used in digital cameras, camcorders, and scanners to create a color image. The filter pattern is half green, one quarter red and one quarter blue, hence is also called BGGR, RGBG, GRBG, or RGGB. It is named after its inventor, Bryce Bayer of Eastman Kodak. Bayer is also known for his recursively defined matrix used in ordered dithering.
Object co-segmentationIn computer vision, object co-segmentation is a special case of , which is defined as jointly segmenting semantically similar objects in multiple images or video frames. It is often challenging to extract segmentation masks of a target/object from a noisy collection of images or video frames, which involves object discovery coupled with . A noisy collection implies that the object/target is present sporadically in a set of images or the object/target disappears intermittently throughout the video of interest.
Intensive and extensive propertiesPhysical properties of materials and systems can often be categorized as being either intensive or extensive, according to how the property changes when the size (or extent) of the system changes. According to IUPAC, an intensive quantity is one whose magnitude is independent of the size of the system, whereas an extensive quantity is one whose magnitude is additive for subsystems. The terms "intensive and extensive quantities" were introduced into physics by German writer Georg Helm in 1898, and by American physicist and chemist Richard C.
