Perception of Light Intensity CSE 332/564: Visualization Fundamentals of Color Klaus Mueller Computer Science Department Stony Brook University How Many Intensity Levels Do We Need? Dynamic Intensity Range Issues Dynamic range of the natural world: 100 000 000:1 Dynamic range the eye can accommodate in a single view: 10 000:1 Dynamic range a typical monitor can display: 100:1 Dynamic range a typical camera can capture: 100:1
Long Camera Exposure Short Camera Exposure captured the interior well, but the outside is too bright captured the outside well, but now the interior is dark Medium Camera Exposure everything is somewhat present, but not very detailed What Now OK.. now we have three images that t have captured all the detail of the scene but we want to visualize it all in one picture, not three we need some way to merge these three pictures this is the domain of High Dynamic Range Imaging (HDR) How does HDR work? Two methods: somehow compress the large range into a small, displayable range look at small neighborhoods and try to maximize contrast in each the first is a global method, the second is a local method This is also often called tone mapping Another application of HDR: computational datasets are often computed in floating point precision HDR can be used to compress the floating point images into 8-bit
Methods Comparison: Global Method Global l methods: scale each pixel according to a fixed curve the key issue is here: the shape of the curve Local methods: group small neighborhoods by their average value scale these averages down add detail back in Comparison: Local Method Result With Earlier Example
References Back to The Optical Illusion Example HDR has become a popular technique Some of the key HDR researchers are: P. Debevec, E. Reinhard, G. Ward, M. Ashikhmin, J. Tumblin, and others for use of HDR in scientific visualization, see X. Yuan, M. Nguyen, B. Chen and D. Porter, High Dynamic Range Volume Visualization, IEEE Transaction on Visualization and Computer Graphics, vol. 12, no. 4, 2006. Image examples were taken from http://www.hdrsoft.comhdrsoft Explanation Spectrum of Wavelengths While the retina can perceive a high h range of intensities, iti it cannot handle all simultaneously at any given time, each region adapts to a small intensity range determined by the local intensity that is why you have to wait a while when you step from a bright into a dark room (say, a dark movie theater from a brightly lit lobby) after moving the eye: eventually adapted range eventually the bright area intensity is unsaturated, matches neighborhood (which was already adapted here before) current adapted after moving the eye: range new bright area saturates intensity perception current dark area in picture falls here
Perception Curves Perceptional Color Spaces human color sensitivity curves color generation with primaries Use Of The CIE Chromaticity Diagram The Munsell Perceptional Color Space Th (i l l h d) M ll t h 3 The (irregularly shaped) Munsell tree has 3 axes: chroma (saturation): distance from the core (values 0-30, with fluorescent colors having the maximum 30) value (brightness): vertical axis (0 10 (white)) hue: 10 principal hues (R, YR, Y, GY, G, BG, B, PB, P, RP)
Non-Perceptional Color Spaces Application: Colorization of Grey-Level Images magenta red blue white cyan green RGB yellow HSV compare to: CIE LAB in 3D Application: Colorization of Grey-Level Images Application: Colorization of Grey-Level Images movie: movie:
References More on Color More information: T. Welsh, M. Ashikhmin, and K. Mueller, "Transferring color to greyscale images," ACM Transactions on Graphics (Proc. of SIGGRAPH'02), vol. 21, no. 3, pp. 277-280, 280 2002. More on Color More on Color
Use of Color Luminance Contrast Luminance Contrast Color Contrast and Harmony
Color Constancy A psychophysical h phenomenon: accounts for the ability of humans to accurately perceive the "color" of an object under different lighting conditions lighting, or illumination, may vary both over a viewed scene and over time yet the perceived color is constant in fact, constant illumination over a scene is almost never encountered in real life Given an object, the colors we perceive (within limits) remain the same, even though the spectral content ("color") of sunlight varies greatly through the day and with weather conditions artificial light sources also vary greatly from one to another Color Constancy: Example illuminant A illuminant B illuminant C Chromatic Aberration Why Color? Color Adds More Dimensions from: J. Döllner, U Potsdam from: M. Stone
Color Adds Aesthetics But Mapping to Color Can Cause Problems from: M. Stone from: M. Stone Color Maps Color Map: Segmentation Tasks
Color Map: Rainbow Color Map: Linear Hue Color Maps: Spatial Frequency Issues Color Maps: Low vs. High Frequency weather model low frequency radar scan high frequency
Color Maps: Highlighting Brewer Scale Nominal scales distinct hues, but similar emphasis Sequential scales vary in lightness and saturation vary slightly in hue Diverging scale complementary sequential scales neutral at zero from: M. Stone (see also colorbrewer.org) Brewer Scales Example for Proper Use of Color from: M. Stone (see also colorbrewer.org)
References Maureen Stone, A Field Guide to Digital it Color, AK Peters 2003 color perception and design with color Colin Ware, Perception and Information Visualization: 2 nd Edition, Morgan Kaufman, 2004 book specifically geared towards information visualization Bernice Rogowitz and Lloyd Treinish, An architecture for perceptual p rule-based visualization, Proc. IEEE Visualization 1993, pp. 236-243, 1993 see also http://www.research.ibm.com/dx/proceedings/pravda/index.htm com/dx/proceedings/pravda/index htm http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm Color brewer: http://www.colorbrewer.org