Digital Image Processing COSC 6380/4393. Lecture 20 Oct 25 th, 2018 Pranav Mantini
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1 Digital Image Processing COSC 6380/4393 Lecture 20 Oct 25 th, 2018 Pranav Mantini
2 What is color? Color is a psychological property of our visual experiences when we look at objects and lights, not a physical property of those objects or lights (S. Palmer, Vision Science: Photons to Phenomenology) Color is the result of interaction between physical light in the environment and our visual system Wassily Kandinsky ( ), Murnau Street with Women, 1908
3 Motivation Visual Descriptor (descriptions of the visual features of the contents) 11/1/2018 3
4 Principal Descriptor Visual Descriptor (descriptions of the visual features of the contents) SHAPE 11/1/2018 4
5 Principal Descriptor Visual Descriptor (descriptions of the visual features of the contents) SHAPE 11/1/2018 5
6 Principal Descriptor Visual Descriptor (descriptions of the visual features of the contents) SHAPE COLOR 11/1/2018 6
7 Principal Descriptor H.R. Pourreza
8 Principal Descriptor H.R. Pourreza
9 Principal Descriptor Visual Descriptor (descriptions of the visual features of the contents) SHAPE COLOR Color is a powerful descriptor that often simplifies object identification and extraction from a scene. 11/1/2018 9
10 Principal Descriptor Visual Descriptor (descriptions of the visual features of the contents) SHAPE COLOR TEXTURE 11/1/
11 Principal Descriptor Visual Descriptor SHAPE COLOR TEXTURE MOTION 11/1/
12 Discerning Color ~1000 ~24
13 Motivation Color is principal descriptor Ability to discern thousands of colors 11/1/
14 Color Image Processing Two majors areas Full color processing
15 Color Image Processing Two majors areas Full color processing
16 Color Image Processing Two majors areas Full color processing Color image
17 Color Image Processing Two majors areas Full color processing Psuedocolor processing
18 Color Image Processing Two majors areas Full color processing Psuedocolor processing Intensity values Thermal Camera
19 Color Image Processing Two majors areas Full color processing Psuedocolor processing Thermal Camera
20 Color Image Processing Two majors areas Full color processing Psuedocolor processing Assign values Thermal Camera Color image
21 Color fundamentals Physical phenomenon Physical nature of color can be expressed on formal basis (using experiments and theoretical results) Physio-psychological phenomenon How human brain perceive and interpret color?
22 Color Fundamentals 1666, Isaac Newton 11/1/
23 Color Fundamentals Six broad regions, each blends into the next smoothly. 11/1/
24 Color fundamentals (cont.) The color that human perceive in an object = the light reflected from the object Illumination source scene eye reflection
25 Color fundamentals (cont.) Balanced in all visible wavelengths white Absorbs all light black Limited range of visible spectrum color shade 500 to 570 nm Green object Illumination source scene eye reflection
26 Characterization of Light Acromatic light has only intensity (or amount) (void of color) Black and white television Gray level: scalar measure of intensity Chromatic light span the electromagnetic spectrum (EM) from 400 to 700 nm
27 Physical quantities to describe a chromatic light source Radiance: total amount of energy that flow from the light source, measured in watts (W) Luminance: amount of energy an observer perceives from a light source, measured in lumens (lm) Far infrared light: high radiance, but 0 luminance Brightness: subjective descriptor that is hard to measure, similar to the achromatic notion of intensity
28 Color Fundamentals Cones are the sensors in the eye that are responsible for color vision 6 to 7 million cones in the human eye Can be divided into three principal sensing categories, corresponding roughly to red, green, and blue. 65%: red 33%: green 2%: blue (blue cones are the most sensitive) 11/1/
29 Color Fundamentals 11/1/
30 Primary colors Due to the absorption characteristics of human eye, Primary colors: Red Green Blue Color: described as a variable combination of the primary colors In 1931, CIE(International Commission on Illumination) defines specific wavelength values to the primary colors B = nm, G = nm, R = 700 nm However, we know that no single color may be called red, green, or blue
31 11/1/
32 Primary colors of light v.s. primary colors of pigments Primary color of pigments Color that subtracts or absorbs a primary color of light and reflects or transmits the other two Color of light: R G B Color of pigments: absorb R absorb G absorb B Cyan Magenta Yellow
33 11/1/
34 Application of additive nature of light Color TV colors
35 Application of subtractive color model Printers: the usual primary colors are cyan, magenta and yellow (CMY) Cyan serves as a filter that absorbs red Amount of cyan applied controls how much of the red in white light will be reflected back Cyan is completely transparent to green and blue light and has no effect on those parts of the spectrum
36 Application of subtractive color model Magenta is the complement of green, and yellow the complement of blue. Combinations of different amounts of the three can produce a wide range of colors with good saturation.
37 Color Fundamentals The characteristics generally used to distinguish one color from another are brightness, hue, and saturation brightness: the achromatic notion of intensity. hue: dominant wavelength in a mixture of light waves, represents dominant color as perceived by an observer. saturation: relative purity or the amount of white light mixed with its hue. 11/1/
38 Why specify color numerically? Accurate color reproduction is commercially valuable Many products are identified by color Few color names are widely recognized by English speakers - About 10; other languages have fewer/more, but not many more. It s common to disagree on appropriate color names. Color reproduction problems increased by prevalence of digital imaging - eg. digital libraries of art. How do we ensure that everyone sees the same color?
39 slide from T. Darrel
40 slide from T. Darrel
41 slide from T. Darrel
42 slide from T. Darrel
43 slide from T. Darrel
44 slide from T. Darrel
45 slide from T. Darrel
46 slide from T. Darrel
47 slide from T. Darrel
48 The principle of trichromacy Experimental facts: Three primaries will work for most people if we allow subtractive matching Exceptional people can match with two or only one primary. This could be caused by a variety of deficiencies. Most people make the same matches. There are some anomalous trichromats, who use three primaries but make different combinations to match.
49 Grassman s Laws Color matching is (approximately) linear symmetry: U=V <=>V=U transitivity: U=V and V=W => U=W proportionality: U=V <=> tu=tv additivity: if any two (or more) of the statements U=V, W=X, (U+W)=(V+X) are true, then so is the third These statements are as true as any biological law. They mean that color matching under these conditions is linear.
50 slide from T. Darrel
51 slide from T. Darrel
52 CIE RGB Tri-stimulus values: Color defined by three value (R,G,B) The amount of Red, Green and Blue needed to form any particular color
53 CIE XYZ New color matching functions were to be everywhere greater than or equal to zero. For the constant energy white point, it was required that x = y = z = 1/3.
54 CIE XYZ model RGB -> CIE XYZ model Normalized tristimulus values Z Y X X x Z Y X Y y Z Y X Z z B G R Z Y X => x+y+z=1. Thus, x, y (chromaticity coordinate) is enough to describe all colors
55 CIE Chromaticity Diagram It shows color composition as a function of x (red) and y (green) 11/1/
56 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 11/1/
57 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y Green: 62% Red: 25% Blue: (1- (62+25))= 13% 11/1/
58 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) 11/1/
59 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) Pure colors 11/1/
60 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) 3. Any point inside the boundary is some mixture of spectrum colors 11/1/
61 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) 3. Any point inside the boundary is some mixture of spectrum colors 4. Point of equal energy (white) 11/1/
62 CIE Chromaticity Diagram 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) 3. Any point inside the boundary is some mixture of spectrum colors 4. Point of equal energy (white) 5. Saturation Boundary to point of equal energy 11/1/
63 CIE Chromaticity Diagram Fully saturated 1. For any value of x, y the value of z can be obtained using z = 1 x + y 2. Boundary various spectrum colors (violet to red) 3. Any point inside the boundary is some mixture of spectrum colors 4. Point of equal energy (white) 5. Saturation Boundary to point of equal energy zero saturated 11/1/
64 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 11/1/
65 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 11/1/
66 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 2. Extend to three points: 11/1/
67 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 2. Extend to three points: Any color in the triangle can be obtained by combing the three vertices 11/1/
68 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 2. Extend to three points: Any color in the triangle can be obtained by combing the three vertices No three points that encompass the entire gamut of colors. 11/1/
69 Color mixing using CIE Chromaticity Diagram 1. Line joining two points: all possible colors possible by combining the two colors 2. Extend to three points: Any color in the triangle can be obtained by combing the three vertices No three points that encompass the entire gamut of colors. All colors cannot be created by adding R, G and B 11/1/
70 Color models Color model, color space, color system Specify colors in a standard way A coordinate system that each color is represented by a single point RGB model CYM model CYMK model HSI model Suitable for hardware or applications - match the human description
71 RGB Color Model 11/1/
72 RGB Color Model Pixel depth The total number of colors in a 24-bit RGB image is (2 8 ) 3 = 16,777,216 11/1/
73 11/1/
74 Safe RGB colors (or safe Web colors) are reproduced faithfully, reasonably independently of viewer hardware capabilities 11/1/
75 11/1/
76 CMY model (+Black = CMYK) CMY: secondary colors of light, or primary colors of pigments Used to generate hardcopy output B G R Y M C 1 1 1
77 The CMY and CMYK Color Models C 1 R M 1 G Y 1 B Equal amounts of the pigment primaries, cyan, magenta, and yellow should produce black. In practice, combining these colors for printing produces a muddy-looking black. To produce true black, the predominant color in printing, the fourth color, black, is added, giving rise to the CMYK color model. 11/1/
78 CMY vs. CMYK 11/1/
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