Digital Color Imaging (Digital Signal and Image Processing)
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The book offers comprehensive coverage of state-of-the-art systems, processing techniques, and emerging applications of digital color imaging.
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To elucidate the significant progress in specialized areas, the editors invited renowned authorities to address specific research challenges and recent trends in their area of expertise. The book begins by focusing on color fundamentals, including color management, gamut mapping, and color constancy. The remaining chapters detail the latest techniques and approaches to contemporary and traditional color image processing and analysis for a broad spectrum of sophisticated applications, including:.
Color Image Processing: Methods and Applications is a versatile resource that can be used as a graduate textbook or as stand-alone reference for the design and the implementation of various image and video processing tasks for cutting-edge applications. Additional material is available at the companion web site www. A book on Color Image Processing! Vector and semantic processing.
A Kodak DCS image rendered without any saturation fix a , with pixel value clipping to a known white point b , and with saturation fix c for an image with a large number of saturated pixels. Estimation of saturated pixel values in digital color imaging. A plot of Red vs Green sensor values for non-saturated pixels randomly selected from an image shown at lower right corner after bilinear demosaicing.
This image is a sub-region of the truck image in. The correlation between the R and G values for this image area is 0. The RG correlation for the full image in is higher 0. Another DCS image rendered without saturation fix a , with pixel value clipping to a known white point b , and with saturation fix c.
An image rendered without saturation fix a , with pixel value clipping to a known white point b , and with saturation fix c. Saturated pixels were generated by adjusting gains and then clipping in the R and G color channels of an original image without any pixel saturation. Comparison of true sensor values vs the saturated-and-fixed sensor values for the red car image in.
In the plot, a pixel value of 1 represent the saturation level. Coulombe and E. Signal Process. II, Analog Digit. Dubois and T. Wong, K. Lyons, D. Evans, R. Velthuys, G. Bochmann, E. Dubois, N. Georganas, G. Neufeld, M. Ozsu, J. Brinskelle, A. Hafid, N. Hutchinson, P. Iglinski, B. Lamont, D. Makaroff, and D. Khansari and E. Konrad, J. Radecki, and E. Khansari, A. Jalali, E. Dubois, and P.
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- Estimation of saturated pixel values in digital color imaging. - PubMed - NCBI?
Khandani, P. Kabal, and E. Theory , vol. Radecki, J.
Automation of multichannel image processing
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Machine Intell. Kabal and E. Bergeron and E. Fortier and E. Sabri, D. Lemay and E. Dubois and W. Dubois and J. COM, pp. IEEE , vol. Netravali and B. Prasada, ed. IEEE Press, Paquin and E. Dubois, M. Sabri, and J. Ouellet and E. Dubois and A.
ASSP, pp. C, pp. Dubois and L. Chiariglione , eds. Elsevier, Bovik, ed. Elsevier Catalog. Lukac , ed. Additional results and software. Gibson, ed. CRC Press catalog. Konrad , "Estimation of 2-D motion fields from image sequences with application to motion-compensated processing," in Motion Analysis and Image Sequence Processing M.
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