Computational Photography
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Computational Photography
Computational photography refers to digital image capture and processing techniques that use digital computation instead of optical processes. Computational photography can improve the capabilities of a camera, or introduce features that were not possible at all with film based photography, or reduce the cost or size of camera elements. Examples of computational photography include in-camera computation of digital panoramas, high-dynamic-range images, and light field cameras. Light field cameras use novel optical elements to capture three dimensional scene information which can then be used to produce 3D images, enhanced depth-of-field, and selective de-focusing (or "post focus"). Enhanced depth-of-field reduces the need for mechanical focusing systems. All of these features use computational imaging techniques. The definition of computational photography has evolved to cover a number of subject areas in computer graphics, computer vision, and applied optics. These areas are ...
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Process Nocomparam
A process is a series or set of activities that interact to produce a result; it may occur once-only or be recurrent or periodic. Things called a process include: Business and management *Business process, activities that produce a specific service or product for customers *Business process modeling, activity of representing processes of an enterprise in order to deliver improvements *Manufacturing process management, a collection of technologies and methods used to define how products are to be manufactured. *Process architecture, structural design of processes, applies to fields such as computers, business processes, logistics, project management *Process costing, a cost allocation procedure of managerial accounting *Process management, ensemble of activities of planning and monitoring the performance of a business process or manufacturing processes *Process management (project management), a systematic series of activities directed towards causing an end result in engineerin ...
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3D Scanner
3D scanning is the process of analyzing a real-world object or environment to collect data on its shape and possibly its appearance (e.g. color). The collected data can then be used to construct digital 3D modelling, 3D models. A 3D scanner can be based on many different technologies, each with its own limitations, advantages and costs. Many limitations in the kind of objects that can be digitization, digitised are still present. For example, optical technology may encounter many difficulties with dark, shiny, reflective or transparent objects. For example, industrial computed tomography scanning, structured-light 3D scanners, Lidar, LiDAR and Time-of-flight camera, Time Of Flight 3D Scanners can be used to construct digital 3D modeling, 3D models, without non-destructive testing, destructive testing. Collected 3D data is useful for a wide variety of applications. These devices are used extensively by the entertainment industry in the production of movies and video games, includ ...
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3D Reconstruction
In computer vision and computer graphics, 3D reconstruction is the process of capturing the shape and appearance of real objects. This process can be accomplished either by active or passive methods. If the model is allowed to change its shape in time, this is referred to as spatio-temporal reconstruction, non-rigid or spatio-temporal reconstruction. Motivation and applications The research of 3D reconstruction has always been a difficult goal. By Using 3D reconstruction one can determine any object's 3D profile, as well as knowing the 3D coordinate of any point on the profile. The 3D reconstruction of objects is a generally scientific problem and core technology of a wide variety of fields, such as Computer Aided Geometric Design (CAGD), computer graphics, computer animation, computer vision, medical imaging, computational science, virtual reality, digital media, etc. For instance, the lesion information of the patients can be presented in 3D on the computer, which offers a new ...
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Broadband Mask
In telecommunications, broadband is wide bandwidth data transmission which transports multiple signals at a wide range of frequencies and Internet traffic types, that enables messages to be sent simultaneously, used in fast internet connections. The medium can be coaxial cable, optical fiber, wireless Internet (radio), twisted pair or satellite. In the context of Internet access, broadband is used to mean any high-speed Internet access that is always on and faster than dial-up access over traditional analog or ISDN PSTN services. Overview Different criteria for "broad" have been applied in different contexts and at different times. Its origin is in physics, acoustics, and radio systems engineering, where it had been used with a meaning similar to "wideband", or in the context of audio noise reduction systems, where it indicated a single-band rather than a multiple-audio-band system design of the compander. Later, with the advent of digital telecommunications, the term was mainly ...
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Well-conditioned Problem
The mathematical term well-posed problem stems from a definition given by 20th-century French mathematician Jacques Hadamard. He believed that mathematical models of physical phenomena should have the properties that: # a solution exists, # the solution is unique, # the solution's behaviour changes continuously with the initial conditions. Examples of archetypal well-posed problems include the Dirichlet problem for Laplace's equation, and the heat equation with specified initial conditions. These might be regarded as 'natural' problems in that there are physical processes modelled by these problems. Problems that are not well-posed in the sense of Hadamard are termed ill-posed. Inverse problems are often ill-posed. For example, the inverse heat equation, deducing a previous distribution of temperature from final data, is not well-posed in that the solution is highly sensitive to changes in the final data. Continuum models must often be discretized in order to obtain a numerical ...
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Motion Blur
Motion blur is the apparent streaking of moving objects in a photograph or a sequence of frames, such as a film or animation. It results when the image being recorded changes during the recording of a single exposure, due to rapid movement or long exposure. Usages / Effects of motion blur Photography When a camera creates an image, that image does not represent a single instant of time. Because of technological constraints or artistic requirements, the image may represent the scene over a period of time. Most often this exposure time is brief enough that the image captured by the camera appears to capture an instantaneous moment, but this is not always so, and a fast moving object or a longer exposure time may result in blurring artifacts which make this apparent. As objects in a scene move, an image of that scene must represent an integration of all positions of those objects, as well as the camera's viewpoint, over the period of exposure determined by the shutter speed. In ...
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Deconvolution
In mathematics, deconvolution is the operation inverse to convolution. Both operations are used in signal processing and image processing. For example, it may be possible to recover the original signal after a filter (convolution) by using a deconvolution method with a certain degree of accuracy. Due to the measurement error of the recorded signal or image, it can be demonstrated that the worse the SNR, the worse the reversing of a filter will be; hence, inverting a filter is not always a good solution as the error amplifies. Deconvolution offers a solution to this problem. The foundations for deconvolution and time-series analysis were largely laid by Norbert Wiener of the Massachusetts Institute of Technology in his book ''Extrapolation, Interpolation, and Smoothing of Stationary Time Series'' (1949). The book was based on work Wiener had done during World War II but that had been classified at the time. Some of the early attempts to apply these theories were in the fields of ...
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Coded Aperture
Coded apertures or coded-aperture masks are grids, gratings, or other patterns of materials opaque to various wavelengths of electromagnetic radiation. The wavelengths are usually high-energy radiation such as X-rays and gamma rays. By blocking radiation in a known pattern, a coded "shadow" is cast upon a plane. The properties of the original radiation sources can then be mathematically reconstructed from this shadow. Coded apertures are used in X- and gamma ray imaging systems, because these high-energy rays cannot be focused with lenses or mirrors that work for visible light. Rationale Imaging is usually done at optical wavelengths using lenses and mirrors. However, the energy of hard X-rays and γ-rays is too high to be reflected or refracted, and simply passes through the lenses and mirrors of optical telescopes. Image modulation by apertures is therefore often used instead. The pinhole camera is the most basic form of such a modulation imager, but its disadvantage is low th ...
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Image Deblurring
Deblurring is the process of removing blurring artifacts from images. Deblurring recovers a sharp image ''S'' from a blurred image ''B'', where ''S'' is convolved with ''K'' (the blur kernel) to generate ''B''. Mathematically, this can be represented as B=S*K (where * represents convolution). While this process is sometimes known as ''unblurring'', ''deblurring'' is the correct technical word. The blur K is typically modeled as point spread function and is convolved with a hypothetical sharp image ''S'' to get ''B'', where both the ''S'' (which is to be recovered) and the point spread function ''K'' are unknown. This is an example of an inverse problem. In almost all cases, there is insufficient information in the blurred image to uniquely determine a plausible original image, making it an ill-posed problem. In addition the blurred image contains additional noise which complicates the task of determining the original image. This is generally solved by the use of a regularizatio ...
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Epsilon Photography
Epsilon photography is a form of computational photography wherein multiple images are captured with slightly varying camera parameters (each image varying the parameter by a small amount ''ε'', hence the name) such as aperture, exposure, focus, film speed and viewpoint for the purpose of enhanced post-capture flexibility. The term was coined by Prof. Ramesh Raskar. The technique has been developed as an alternative to light field photography that requires no specialized equipment. Examples of epsilon photography include focal stack photography, High dynamic range (HDR) photography, lucky imaging, multi-image panorama stitching and confocal stereo. The common thread for all the aforementioned imaging techniques is that multiple images are captured in order to produce a composite image of higher quality, such as richer color information, wider-field of view, more accurate depth map, less noise/blur and greater resolution. Since Epsilon photography at times may require the captu ...
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Bidirectional Reflectance Distribution Function
The bidirectional reflectance distribution function (BRDF; f_(\omega_,\, \omega_) ) is a function of four real variables that defines how light is reflected at an opaque surface. It is employed in the optics of real-world light, in computer graphics algorithms, and in computer vision algorithms. The function takes an incoming light direction, \omega_, and outgoing direction, \omega_ (taken in a coordinate system where the surface normal \mathbf n lies along the ''z''-axis), and returns the ratio of reflected radiance exiting along \omega_ to the irradiance incident on the surface from direction \omega_. Each direction \omega is itself parameterized by azimuth angle \phi and zenith angle \theta, therefore the BRDF as a whole is a function of 4 variables. The BRDF has units sr−1, with steradians (sr) being a unit of solid angle. Definition The BRDF was first defined by Fred Nicodemus around 1965. The definition is: f_(\omega_,\, \omega_) \,=\, \frac \,=\, \frac\frac wher ...
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