Chapter 8 Computer Vision Artificial IntelligenceChapter 92 Contents What is Image Processing? Digital Image Processing Electromagnetic Spectrum Steps in Digital Image Processing Artificial IntelligenceChapter 93 What is Image Processing? Artificial IntelligenceChapter 94 Application Area Artificial IntelligenceChapter 95 Image Processing Fields Artificial IntelligenceChapter 96 Image Processing Fields Artificial IntelligenceChapter 97 Digital Image Processing Digital Image ? Digital Image Image Processing ? Artificial IntelligenceChapter 98 Digital Image Processing What is a signal? A signal is a function that maps a set (domain) to another set (range) Artificial IntelligenceChapter 99 Digital Image Processing A signal is a function that maps a set (domain) to another set (range) For each point in time (t), assign a voltage value (y(t)). Domain = time interval Range = voltage interval Artificial IntelligenceChapter 910 Digital Image Processing Image An image is a two-dimensional signal A signal is called two-dimensional if the domain is two-dimensional Artificial IntelligenceChapter 911 Digital Image Processing Image An image is a two-dimensional signal Artificial IntelligenceChapter 912 Digital Image Processing Digital Image Vs Analog image? Digital vs analog signal Artificial IntelligenceChapter 913 Signal Types Domain Range Countable Quantized Signal UncountableCountable Continuous-time Continuous-space Discrete-time Discrete-space Artificial IntelligenceChapter 914 Digital Signal A signal is digital if both the domain and the range are countable I.e., if it is a quantized discrete-time (or -space) signal Artificial IntelligenceChapter 915 Digital Image Processing Digital Image A digital image is a two-dimensional signal with a countable domain and a countable range Artificial IntelligenceChapter 916 Digital Image Processing Digital Image Artificial IntelligenceChapter 917 Digital Signal How is a digital signal formed? Discrete domain Domain is inherently discrete, or Sample a continuous interval Discrete range Range is inherently discrete, or Sample a continuous interval Artificial IntelligenceChapter 918 Domain and Range Continuous-time signals t and y (t) have physical meanings Digital signals n and y (n) do not have physical meanings and can be arbitrary Artificial IntelligenceChapter 919 Digital Image Processing Fields Artificial IntelligenceChapter 920 Digital Images: 80 years ago Range has 5 values! Artificial IntelligenceChapter 921 Electromagnetic Spectrum : EM Artificial IntelligenceChapter Gamma-Ray Imaging Artificial IntelligenceChapter X-ray Imaging Artificial IntelligenceChapter UV Imaging Artificial IntelligenceChapter Visible Range Artificial IntelligenceChapter Visible Range 1964 Artificial IntelligenceChapter Visible Range Artificial IntelligenceChapter Multispectral: Visible+Infrared Bands Artificial IntelligenceChapter Multispectral: Visible+Infrared Bands Artificial IntelligenceChapter Multispectral: Visible+Infrared Bands Artificial IntelligenceChapter Multispectral: Visible+ Infrared Bands Artificial IntelligenceChapter Infrared Range Artificial IntelligenceChapter Microwave Imaging: Radar Artificial IntelligenceChapter Radio Band Imaging Artificial IntelligenceChapter 935 Electromagnetic Spectrum Artificial IntelligenceChapter 936 Artificial IntelligenceChapter 937 Ultrasound Image head Artificial IntelligenceChapter 938 Artificial IntelligenceChapter 939 Artificial IntelligenceChapter 940 Steps in Digital Image Processing Artificial IntelligenceChapter 941 1 Artificial IntelligenceChapter 942 2 Artificial IntelligenceChapter 943 Distorted imageRestore image 3 Artificial IntelligenceChapter 944 4 Artificial IntelligenceChapter 945 5 Artificial IntelligenceChapter 946 6 Artificial IntelligenceChapter 947 7 Artificial IntelligenceChapter 948 8 Artificial IntelligenceChapter 949 9 Artificial IntelligenceChapter 950 9 Artificial IntelligenceChapter Artificial IntelligenceChapter 952 Knowledge Base 11 Image Enhancement in the Spatial Domain Artificial IntelligenceChapter 954 Contents Spatial Domain Point Process Transformation functions Histogram Spatial Filtering Mask Operation Image Enhancement Smoothing Filter Artificial IntelligenceChapter 955 Spatially Varying Signal Artificial IntelligenceChapter 956 Spatiotemporal Signals Artificial IntelligenceChapter 957 Image Processing An image processing system maps an input image to an output image Input images Output images Artificial IntelligenceChapter 958 Image Processing Output pixel depends on the input image pixels Usually: Artificial IntelligenceChapter 959 Transformation function s= T [r] 1. contrast stretching 2. point processing : Thresholding Function Transformation functions Artificial IntelligenceChapter 960 Transformation functions Artificial IntelligenceChapter 961 Transformation functions s= T [r] r s dark light light dark Artificial IntelligenceChapter 962 Transformation functions s= L-1 -r negative transformationoriginal image Artificial IntelligenceChapter 963 s= c r = 3 = 4 = 5 Power-Law Transformations Artificial IntelligenceChapter 964 Contrast Stretching Artificial IntelligenceChapter 965 Histogram Count the number of pixels with each gray level Artificial IntelligenceChapter 966 Histogram Artificial IntelligenceChapter 967 Histogram Artificial IntelligenceChapter 968 Artificial IntelligenceChapter 969 Histogram Equalization Artificial IntelligenceChapter 970 Histogram Equalization Artificial IntelligenceChapter 971 Histogram Equalization Artificial IntelligenceChapter 972 Spatial Filtering Pixels Artificial IntelligenceChapter 973 Laplacian Output Artificial IntelligenceChapter 974 Image Enhancement Artificial IntelligenceChapter 975 Image Enhancement Image Segmentation Artificial IntelligenceChapter 977 Line Detection horizontal, degree,.. vertical... and -45 degree masks Horizontal mask will result with max response when a line passed through the middle row of the mask with a constant background. the similar idea is used with other masks. note: the preferred direction of each mask is weighted with a larger coefficient....(i.e.,2) than other possible directions. Artificial IntelligenceChapter 978 Example Artificial IntelligenceChapter 979 Example Artificial IntelligenceChapter 980 link criteria: 1). the pixels belonged to one of the set of pixels linked according to the highest count 2). no gaps were longer than 5 pixels Artificial IntelligenceChapter 981 Result of applying T Artificial IntelligenceChapter 982 Thresholds based on several variables (multispectral thresholding) Artificial IntelligenceChapter 983 The End