By Gaurav Sharma, Raja Bala
Electronic expertise now permits extraordinary performance and suppleness within the trap, processing, trade, and output of colour pictures. yet harnessing its power calls for wisdom of colour technological know-how, structures, processing algorithms, and equipment characteristics-topics drawn from a wide diversity of disciplines. it is easy to collect the needful heritage with an armload of physics, chemistry, engineering, desktop technological know-how, and arithmetic books and journals- or you will find it right here, within the electronic colour Imaging Handbook.
Unprecedented in scope, this instruction manual offers, in one concise and authoritative ebook, the weather of those assorted parts correct to electronic colour imaging. the 1st 3 chapters hide the fundamentals of colour imaginative and prescient, notion, and physics that underpin electronic colour imaging. the rest of the textual content provides the know-how of colour imaging with chapters on colour administration, gadget colour characterization, electronic halftoning, photograph compression, colour quantization, gamut mapping, computationally effective rework algorithms, and colour snapshot processing for electronic cameras.
Each bankruptcy is written by way of world-class specialists and mostly self-contained, yet go references among chapters replicate the themes' vital interrelations. Supplemental fabrics can be found for obtain from the CRC site, together with digital models of a few of the pictures offered within the booklet.
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Extra resources for Digital Color Imaging Handbook (Electrical Engineering & Applied Signal Processing Series)
32) where f(·),Xn, Yn, and Zn are as deﬁned earlier. Because CIELAB is used extensively in imaging, transforms to and from CIELAB to other color spaces are commonly employed. 40) serves as a correlate or measure of perceived chroma. 41) serves as a correlate of perceived hue. Euclidean distance between two color stimuli in CIELAB space is denoted by ∆E*ab (delta E-ab). 42) where ∆L* = L*2 – L*s , ∆a* = a*2 – a*s , and ∆b* = b*2 – b*s are the distances of the sample from the standard along the L*, a*, and b* axes, respectively.
This ensures that the distance between two samples is independent of which one is chosen as the standard. 47 is referred to as the ∆E*94 color difference. The CIE-94 color difference formula is signiﬁcantly simpler than the CMC formula. 54, it is clear that the CIE-94 color difference formula scales down hue and chroma differences for higher chroma colors in comparison to CIELAB and thus corrects for the predominant deﬁciency in CIELAB. Along the L* axis, the scaling factors are all unity, which ensures that (asymmetric) ∆E*94 color differences about neutral colors that lie on the L* axis are identical to the ∆E*ab Euclidean color difference.
Understandably, the most signiﬁcant artifacts are seen in the blue region, and the most common instantiation is the shift from blue to purple in the mapping of colors in the vicinity of the CRT blue primary to a printer gamut. More recently, the problem has been addressed by either warping the CIELAB space to correct for the hue “nonlinearity” before the gamut mapping33 or through the use of alternate spaces, other than CIELAB, that provide better correlates of hue. Details are included in the chapter on gamut mapping.