This document discusses estimating information from image colors and its application to digital cameras and natural scenes. It aims to derive estimators of the information available and retrieved from color values in images under different illuminations. The estimators were applied to simulations of images from five digital camera sensor sets and human eye cone photoreceptors using 50 hyperspectral natural scene images under daylight illuminants of varying color temperatures. Depending on the sensor set, the estimated mean information available across illuminations ranged from 15.5 to 18.0 bits, while the estimated mean information retrieved after processing ranged from 13.2 to 15.5 bits, representing about 85% of the available information. The best sensor set allowed identifying 390% more points per scene than the worst

1. ECWAY TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE
BANGALORE / HYDRABAD
CELL: +91 98949 17187, +91 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 / 8111
VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com
ESTIMATING INFORMATION FROM IMAGE COLORS AN APPLICATION TO
DIGITAL CAMERAS AND NATURAL SCENES
ABSTRACT:
The colors present in an image of a scene provide information about its constituent elements. But
the amount of information depends on the imaging conditions and on how information is
calculated. This work had two aims. The first was to derive explicitly estimators of the
information available and the information retrieved from the color values at each point in images
of a scene under different illuminations. The second was to apply these estimators to simulations
of images obtained with five sets of sensors used in digital cameras and with the cone
photoreceptors of the human eye. Estimates were obtained for 50 hyperspectral images of natural
scenes under daylight illuminants with correlated color temperatures 4,000, 6,500, and 25,000 K.
Depending on the sensor set, the mean estimated information available across images with the
largest illumination difference varied from 15.5 to 18.0 bits and the mean estimated information
retrieved after optimal linear processing varied from 13.2 to 15.5 bits (each about 85 percent of
the corresponding information available). With the best sensor set, 390 percent more points
could be identified per scene than with the worst. Capturing scene information from image colors
depends crucially on the choice of camera sensors.