color.slides.printing.2 - CS 450: Introduction to Digital...

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Unformatted text preview: CS 450: Introduction to Digital Signal and Image Processing Color Processing Light and Wavelengths • Visible light is in the range 400 nm (blue) to 700 nm (red). Perception of Light • Cones have three different kinds of color-sensitive pigments, each responding to a different range of wavelengths. • These are roughly “red”, “green”, and “blue” in their peak response but each responds to a wide range of wavelengths. • The combination of the responses of these different receptors gives us our color perception. • This is called the tristimulus model of color vision. Cones and Wavelengths (From G&W, individual cone responses normalized) Cones and Wavelengths • The sensitivity and number of the three types of cones are different • More sensitive overall to green and red than to blue Relative responses of the three different cones Luminous Efficiency Function • The luminous efficiency function combines the responses of all three to measure perceived brightness for different wavelengths RGB Color Model • Simplest model is just to store red, green, and blue values • Colors can be thought of as points in a RGB cube RGB Color Channels “Web Safe” Colors Primaries and Secondaries • Primary colors: ones mixed to make other colors • Secondary colors: pairwise combinations of primaries • Can be additive or subtractive CMY Model • Subtractive media absorb rather than emit light – Real-world objects – Paint – Printing ink • The perceived color is what is not absorbed (reflected) • CMY based on subtractive primaries: cyan (C), magenta (M), and yellow (Y) CMYK Model • Problem with CMY model: – Because of imperfect primaries, can’t entirely absorb all colored light (i.e., make black) – Usually produces a dark greyish brown • Solution: add black (K) as a fourth primary • CMYK most common model for printers Luminance and Chromaticity • RGB and CMYK aren’t the most intuitive model of colors. • Artists usually think of dark/light and color as two different things: – Luminance (brightness) – Chromaticity (color) Luminance • Technically, – Luminance = incoming light – Brightness = perceived incoming light • Many color models make the luminance or brightness an explicit component of the color model though by varying names: – – – – – – Luminance Intensity Brightness Lightness Luma Value Chromaticity • Requires two parameters – Usually: • Hue • Saturation The dominant wavelength How pure that color is (ratio of color to white) – Some models use different chromaticity parameters • Examples: – Red vs. Blue? – Red vs. Pink? – Dark red vs. Bright red? Tints and Shades • Lightening or darkening colors: – Tint: adding more white to a color – Shade: adding more black to a color • Tints and shades are not inverses! – Why not? The CIE RGB Model • Standardized “red”, “green”, and “blue” to try to match perception: 438.1, 546.1, and 700 mn R = Km G = Km B = Km Ú L(l) r(l) dl Ú L(l) g(l) dl Ú L(l) b(l) dl Notice negative weight of red component for † wavelengths near 500 nm—can’t physically mix The CIE XYZ Model (1931) • Replaces R, G, B with “imaginary” primaries X, Y, Z – Don’t correspond to single wavelengths – Weights are always positive – More saturated than monochromatic light – Can model all physically realizable colors X = Km Y = Km Z = Km † Ú L(l) x (l) dl Ú L(l) y (l) dl Ú L(l) z (l) dl Normalizing CIE XYZ Model • Normalize X, Y, Z so that we can talk about chromaticity: X X +Y + Z Y y= X +Y + Z Z z= X +Y + Z x= † Notice that x + y + z = 1 forms a plane in color space — can just use x and y (because z = 1 - x - y) CIE Chromaticity Diagram Gamut Color Gamuts • A color gamut is the space of colors spanned by a set of primaries • No three physical primaries can span the entire space of physically realizable colors – Use “negative” weights for some colors, or – Use “imaginary” primaries that lie outside the color space – Both are physically impossible • Better with more primaries, but still not able to span the entire color space – Some color printers use more than just CMYK Device Primaries and Gamuts • Different devices have different primaries and different gamuts – Scanners – Monitors – Printers • Two major problems working with color: – Calibration: “talking the same color language” – Out-of-gamut limitations NTSC YIQ Model • The National Television Standards Committee (NTSC) standard uses a color model called YIQ: – Y luminance – I and Q chromaticity ÈY ˘ È0.299 0.587 0.114˘ÈR ˘ Í˙ Í ˙Í ˙ ÍI ˙ = Í0.596 -0.275 -0.321˙ÍG˙ ÍQ˙ Í0.212 -0532 0.311˙ÍB ˙ Î˚ Î ˚Î ˚ • Television Signals – Color TV broadcasts are YIQ †– “Black-and-white” (grey) TV uses Y only HSI Color Model • One axis is intensity (luminance) • The plane perpendicular to this axis represents chromaticity – Angle = hue – Distance from center = saturation • Can map this plane using a triangle, hexagon, or circle HSI Color Model HSI Color Model HSI Color Model Other Color Models • Hue-Saturation-Value (HSV) – Like HSI but with only one cone • • • • Hue-Lightness-Saturation (HLS) Hue-Value-Chroma (HVC) CIE LUV CIE La*b* – Attempts to be perceptually linear Pseudocolor (Indexed Color) • For some applications, you may want to store fewer than 24 bits per pixel – Older/less-expensive video buffers – Compression (used in GIF compression) • Use a lookup table to map values in the image buffer to 24-bit color values – Example: 8-bit buffer, 256-color lookup table – The set of displayable colors in the lookup table is often called the palette • Selection of palette from an image is known as color quantization Pseudocolor (Indexed Color) • Can use similar method for mapping grey level image to color Color and Visualization • Color can be used in information visualization to provide an additional dimension Color and Visualization • Specific color meanings: keep it limited • Color scales are hard to interpret – Heat scale is one that of the few that partially works • Limits of color reproduction can change the message Color Image Processing • General approaches – Process RGB color planes separately • Simple • Not always meaningful thinking in RGB – Convert to HSI or other color space with explicit intensity component • Process the intensity component as you normally would • May process the saturation • Generally want to leave the hue alone in this model – Design transformation in intensity/chromaticity space, but implement through direct RGB manipulation Processing RGB Planes Processing Other Components Color Transformations Color Transformations • Can change channels together to transform the intensities Color Balancing • Or you can change channels separately – Can emphasize or de-emphasize one or more channels Color Histogram Equalization • Convert to HSI or similar space • Process – Histogram equalize the intensity plane – Increase the saturation – Leave the hue plane unchanged • Convert back to RGB for display Color Histogram Equalization Summary • Pick a color space that makes sense for your application • If the application is interactive, consider using HSI or other color space with explicit intensity/chromaticity • If you want to process intensities but keep hues the same, work (or at least think) in that kind of color space • Keep physical limitations in mind – Primaries, different color gamuts, etc. • There’s a lot more to color than RGB triplets! ...
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