Editing Computational photography (section)

{{short description|Set of digital image capture and processing techniques}}
{{broader|Computational imaging}}
[[Image:Process nocomparam.png|thumb|upright=1.25|Computational photography provides many new capabilities. This example combines HDR (High Dynamic Range) imaging with panoramics ([[image-stitching]]), by optimally combining information from multiple differently exposed pictures of overlapping subject matter.<ref>[[Steve Mann (inventor)|Steve Mann]]. "Compositing Multiple Pictures of the Same Scene", Proceedings of the 46th Annual Imaging Science & Technology Conference, May 9–14, Cambridge, Massachusetts, 1993</ref><ref>S. Mann, C. Manders, and J. Fung, "[http://eyetap.org/about_us/people/corey/icassp2003.pdf The Lightspace Change Constraint Equation (LCCE) with practical application to estimation of the projectivity+gain transformation between multiple pictures of the same subject matter]" IEEE International Conference on Acoustics, Speech, and Signal Processing, 6–10 April 2003, pp III - 481-4 vol. 3.</ref><ref>[https://www.researchgate.net/profile/Steve_Mann9/publication/2443973_Pencigraphy%27_with_AGC_Joint_parameter_estimation_in_both_domain_and_range_of_functions_in_same_orbit_of_the_projective-wyckoff_group/links/54da46700cf233119bc266cf.pdf joint parameter estimation in both domain and range of functions in same orbit of the projective-Wyckoff group]" ", IEEE International Conference on Image Processing, Vol. 3, 16-19, pp. 193-196 September 1996</ref><ref>Frank M. Candocia: [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.9241&rep=rep1&type=pdf Jointly registering images in domain and range by piecewise linear comparametric analysis]. IEEE Transactions on Image Processing 12(4): 409-419 (2003)</ref><ref>Frank M. Candocia: [https://web.archive.org/web/20190308113917/http://pdfs.semanticscholar.org/e7b6/a290f99b13c13761002e2284219944f4455c.pdf Simultaneous homographic and comparametric alignment of multiple exposure-adjusted pictures of the same scene]. IEEE Transactions on Image Processing 12(12): 1485-1494 (2003)</ref>]]

'''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]],<ref>Steve Mann and R. W. Picard. "[https://pdfs.semanticscholar.org/c005/6675c407412dc3b4bba375a033eee9d13453.pdf Virtual bellows: constructing high-quality stills from video].", In Proceedings of the IEEE First International Conference on Image ProcessingAustin, Texas, November 13–16, 1994</ref> [[high-dynamic-range imaging|high-dynamic-range images]], and [[light field camera]]s. 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|depth-of-field]], and selective de-focusing (or "post focus"). Enhanced depth-of-field reduces the need for mechanical [[focus (optics)|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 given below, organized according to a taxonomy
proposed by [[Shree K. Nayar]]{{citation needed|date=November 2017}}.  Within each area is a list of techniques, and for
each technique one or two representative papers or books are cited.
Deliberately omitted from the
taxonomy are [[image processing]] (see also [[digital image processing]])
techniques applied to traditionally captured
images in order to produce better images.  Examples of such techniques are
[[image scaling]], dynamic range compression (i.e. [[tone mapping]]),
[[color management]], image completion (a.k.a. inpainting or hole filling),
[[image compression]], [[digital watermarking]], and artistic image effects.
Also omitted are techniques that produce [[3D scanner|range data]],
[[voxel|volume data]], [[3D model]]s, [[light field|4D light fields]],
4D, 6D, or 8D [[Bidirectional reflectance distribution function|BRDF]]s, or other high-dimensional image-based representations. [[Epsilon photography]] is a sub-field of computational photography.