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Image Perception ‘Let there be light! ‘. “Let there be light”

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Presentation on theme: "Image Perception ‘Let there be light! ‘. “Let there be light”"— Presentation transcript:

1 Image Perception ‘Let there be light! ‘

2 “Let there be light”

3 Image perception “Let there be light”

4 ELECTROMAGNETIC SPECTRUM AND VISIBLE BAND Can perceive 7% Cycle per second

5 Human Visual System Eye-Brain Channel brain eye Low level Acquisition Sampling Quantization Enhancement Restoration Compression High Level Enhancement + Restoration+ Compression+ Feature Extraction Labeling Understanding

6 EYE: Diameter:20mm Pupil 2mm Fovea: Sensors,rodes and cones A Feedback Control System: Adjusts the diameter of Eye ball Pupil Lenz

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8 Sampling and quantization around the Fovea Cones: 6-7 million, located mostly on fovea, sensitive to color, each one is connected to a nerve cell Rodes:75-150 million, distributed over retina, sensitive to shape info, several of them is connected to the same nerve cell

9 RODES 80-100 Million for Shape perception

10 CONES: 6-7 Million For color perception CONES: 6-7 Million For color perception

11 Cones:6-7 Milion

12

13

14 In the Brain (60-70% is for vision)

15 In the Brain Gestalt Theory (Koffka 1935) ART (Grosberg, 1978) LGN: Feature extraction, classification, texture analysis, recognition. Visual Cortex: –Scene representation –Interpretation –Knowledge manipulation –Hierarchical library of indexed feature –Task related to hierarchical vision

16 Lateral Geniculate Nucleus Primary Visual Cortex

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18 CHARATERSITICS OF HVS RESOLUTION: Ability to separate 1.Two adjacent pixels: Spatial Resolution 2.Two colors: Radiometric resolution 3.Two frames: Time resolution Response of HVS to resolution depends on the 1.Distance from the eye 2.Illumination

19 Low frequency High frequency f=2 f= 4 x direction 1.Spatial resolution

20 Field of viev Resolution is restricted by physical size of rodes and cones sampling rate of image

21 2. Radiometric resolution: Response to intensity and color Pupil changes size according to the brightnes level What you see is different then what it is dark Glare limit quantization

22 Brightness adaptation is logarithmic function of intensity

23 Weber’s law: weber ratio =  I/I I: intensity,  I: increment of discriminable illumination Weber’s law: weber ratio =  I/I I: intensity,  I: increment of discriminable illumination rodes cones

24 MACH BAND EFFECT (Ernst Mach)

25 Simultaneous Contrast: backroun effect the color of the object

26 3. Temporal resolution response of HVS as a function of time Flicker frequency: ability to observe a flicker Depends on the brightness: 50 hertz

27 Visual Perception- Illusions

28 Simultaneous Contrast

29

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31 HVS: Visual Illusion From Prof. E. H. Adelson

32 What is this? HVS: Visual Illusion

33 Which lines are straight? HVS: Visual Illusion

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35 İmage acquisition devices Three types –Single sensor (scanners) –Sensor stripes (xerox, tomography), circular sensor stripes –Sensor arrays (cameras)

36 İmage acquisition: current technology

37 Chapter 2: Digital Image Fundamentals

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39 Emerging technology: Single pixel camera Compressive sensing

40 Image Representation Continuous image: f(x,y), d= (x,y), r: Brightness values Digital image: both d and r is discrete Discrete image d is discrete, r is continuos Motion: f(x,y,t) Binary image: r  (0,1) Gray scale image r  (0.1,.......L-1) Color image f i (x,y), i=r,g,b Multispectral image: f i (x,y)

41 IMAGE SAMPLING: Digitize the domain of f(x,y) Generate an NxM matrix. How: Study sampling theorem IMAGE SAMPLING: Digitize the domain of f(x,y) Generate an NxM matrix. How: Study sampling theorem

42 IMAGE QUANTIZATION: Digitize the range of f(x,y)

43 Sampled and quantized image

44 f(x,y): storage space: NxMxkxT T: number of frames Number of gray values: L=2 k: f(x,y): storage space: NxMxkxT T: number of frames Number of gray values: L=2 k:

45 Storage Spaces: S= NxMxkxi i= # of bands L=2 k Storage Spaces: S= NxMxkxi i= # of bands L=2 k

46 SAMPLING

47

48 QUANTIZATION

49 Chapter 2: Digital Image Fundamentals

50 HOW TO SELECT SAMPLING AND QUANTIZATION RATES? HOW TO SELECT SAMPLING AND QUANTIZATION RATES?

51 Chapter 2: Digital Image Fundamentals

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53

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55 Storage Spaces: S= NxMxkxi i= # of bands L=2 k Storage Spaces: S= NxMxkxi i= # of bands L=2 k

56 Chapter 2: Digital Image Fundamentals

57

58

59 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

60 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

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62 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

63 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

64 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

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68 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

69 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

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74 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

75 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

76 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

77 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

78 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

79 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

80 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

81 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

82 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

83 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

84 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

85 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

86 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

87 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

88 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

89 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

90 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

91 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

92 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

93 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

94 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

95 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

96 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

97 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

98 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

99 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

100 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

101 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

102 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

103 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

104 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

105 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

106 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

107 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

108 RODES 80-100 Million for Shape perception

109 CHARATERSITICS OF HVS RESOLUTION: Ability to separate –Two adjacent pixels: Spatial Resolution –Two colors: Radiometric resolution –Two frames: Time resolution Response of HVS to resolution depends on the –Distance from the eye –Illumination

110 Chapter 2: Digital Image Fundamentals

111 MACH BAND EFFECT: Sudden changes in gray level accentuates the edges

112 In the Brain Gestalt Theory (Prepare an assay) Occipital Cortex: Feature extraction, classification, texture analysis, recognition. Association Cortex: Koffka 1935 –Scene representation –Interpretation –Knowledge manipulation –Hierarchical library of indexed feature –Task related to hierarchical vision

113 Image acquisition devices

114 Chapter 2: Digital Image Fundamentals

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116 Image Representation Continuous image: f(x,y), d= (x,y), r: Brightness values Digital image: both d and r is discrete

117 Chapter 2: Digital Image Fundamentals

118 Color Image Processing

119 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

120 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

121 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

122 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

123 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

124 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

125 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

126 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

127 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

128 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

129 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

130 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

131 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

132 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

133 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

134 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

135 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

136 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

137 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

138 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

139 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

140 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

141 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

142 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

143 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

144 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

145 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

146 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

147 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

148 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

149 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

150 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

151 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

152 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

153 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

154 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

155 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

156 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

157 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

158 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

159 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

160 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

161 Chapter 6 Color Image Processing Chapter 6 Color Image Processing

162 DIGITIZED IMAGE AND ITS PROPERTIES


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