image fidelity
Image fidelity, often referred to as the ability to discriminate between two images{{Cite book|last1=Silverstein|first1=D. A.|last2=Farrell|first2=J. E.|title=Proceedings of 3rd IEEE International Conference on Image Processing |chapter=The relationship between image fidelity and image quality |date=September 1996|chapter-url=https://ieeexplore.ieee.org/document/559640/;jsessionid=vJInwaQd94WPmGqLdzG6zFJmCAfUpeVM_RgcRixqDFRW6Sgbc2D1!1177258282|volume=1|pages=881–884 vol.1|doi=10.1109/ICIP.1996.559640|isbn=0-7803-3259-8|s2cid=17711937}} or how closely the image represents the real source distribution.{{Cite journal|title=2000ASPC..217..344W Page 344|url=http://articles.adsabs.harvard.edu/cgi-bin/nph-iarticle_query?bibcode=2000ASPC..217..344W&db_key=AST&page_ind=0&plate_select=NO&data_type=GIF&type=SCREEN_GIF&classic=YES|access-date=2020-12-03|journal=Imaging at Radio Through Submillimeter Wavelengths|bibcode = 2000ASPC..217..344W | last1=Wright | first1=M. | year=2000 | volume=217 | page=344 }} Different from image quality, which is often referred to as the subject preference for one image over another, image fidelity represents to the ability of a process to render an image accurately, without any visible distortion or information loss. The two terms are often used interchangeably, but they are not the same.{{Cite book|last1=Silverstein|first1=D. A.|last2=Farrell|first2=J. E.|title=Proceedings of 3rd IEEE International Conference on Image Processing |chapter=The relationship between image fidelity and image quality |date=September 1996|chapter-url=https://ieeexplore.ieee.org/document/559640/;jsessionid=yg8nv6CugJfFccgfhFDFU37OCcrdhEejT-sQbrnfs-TbcB7wwlGf!1177258282|volume=1|pages=881–884 vol.1|doi=10.1109/ICIP.1996.559640|isbn=0-7803-3259-8|s2cid=17711937}}
If we cannot detect the difference between a photograph and a digitally printed image, we might conclude that the digital print has photographic image quality.{{Cite book|last1=Silverstein|first1=D. A.|last2=Farrell|first2=J. E.|title=Proceedings of 3rd IEEE International Conference on Image Processing |chapter=The relationship between image fidelity and image quality |date=September 1996|chapter-url=https://ieeexplore.ieee.org/document/559640/;jsessionid=ORknxfw3C1LXbAE3rS04SA3pLGNYFMQoBNV55ujUdmZevRPIRVfV!614573127|volume=1|pages=881–884 vol.1|doi=10.1109/ICIP.1996.559640|isbn=0-7803-3259-8|s2cid=17711937}} But subjective impressions of image quality are much more difficult to characterize and, consequently, nearly impossible to quantify. It is not difficult to demonstrate that people use multiple visual factors or dimensions in complex non-linear combinations to make judgements about image quality.{{Cite web|title=IMAGE QUALITY: A MULTIDIMENSIONAL PROBLEM|url=https://human-factors.arc.nasa.gov/publications/Ahumada_Null_1993.pdf|website=NASA}} There are also significant individual differences in their judgements.{{Cite book|title=Multidimensional Scaling: Theory and Applications in the behavioral sciences|publisher=Seminar Press|year=1972|isbn=978-0127857817|location=New York|pages=105–156}}
Image fidelity in photography
In photography, image fidelity is also referred to as micro-contrast or 3D pop. The inner tonal rendition of an image could be found as more shades and details are rendered.
There are three ways to increase image fidelity.{{Cite web|title=The FACTS of IMAGE FIDELITY & its existence|url=https://www.youtube.com/watch?v=FhrJ_1YN7FQ|website=Youtube}}
The first is to adopt a high transmission lens on the camera. Lenses with high transmissive characteristics can direct more light into the sensors.
The second is to increase the sensor saturation. There are two ways do this:
- Reduce the thickness of the filter array on the camera sensor so that more low-gain light can be recorded
- Increase the light on the subject so that the sensors are more saturated.
The latter is more common. Flash is usually the method used to achieve it.
Third, reducing or removing the color filter array on a camera sensor. To remove or reduce the thickness of the filter array on the camera sensor so that more low-gain light can be recorded.{{Cite web|last=Design|first=Wild Dog|date=2017-09-22|title="Monochroming" a colour sensor and colour photography with the Monochrom - Wild Dog Design|url=https://wilddogdesign.co.uk/blog/monochroming-colour-sensor-colour-photography-monochrom/|access-date=2020-12-03|language=en-GB}} This process is also called "Debayering a sensor".{{Cite web|last=Design|first=Wild Dog|date=2017-09-22|title="Monochroming" a colour sensor and colour photography with the Monochrom - Wild Dog Design|url=https://wilddogdesign.co.uk/blog/monochroming-colour-sensor-colour-photography-monochrom/|access-date=2020-12-03|language=en-GB}}
References
Further reading
- Yannick Khong, Micro-Contrast, the biggest optical luxury of the world https://yannickkhong.com/blog/2016/2/8/micro-contrast-the-biggest-optical-luxury-of-the-world
- Zhou Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," in IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, April 2004, doi: 10.1109/TIP.2003.819861.
__FORCETOC__