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Published byMarilynn Shields Modified over 9 years ago
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DIGITAL IMAGE PROCESSING CMSC 150: Lecture 14
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Conventional Cameras Entirely chemical and mechanical processes Film: records a chemical record of light pattern Light-sensitive grains in chemical suspension on plastic Upon light exposure, grains undergo reaction Development: expose film to other chemicals Chemicals dye the layers of red, green, blue Overlay to get full-color negative
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Conventional Cameras
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Digital Cameras Sensor converts light to electrical charges 2D array of many tiny cells Light hits, converted into electrons Charge is converted into binary form CCD: Charge Coupled Device
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Analog to Digital Conversion: Sampling
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Digital Image Sensor: 2D array of values Image: "value" stored for cell in the sensor Pixel: picture element One pixel per sensor cell
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Capturing Color Color filter placed over sensor Color at each cell determined as "average of neighbor cells" (How Stuff Works animation)How Stuff Works animation
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Grayscale vs. Color Grayscale: pixel corresponds to shade of gray Highest value: white Lowest value: black
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Grayscale Images: Example PGM: Portable Graymap Use 8-bits per pixel 256 total graylevels, 0-255 Each pixel represented by an integer 0: black 255: white Let's play around with a few, using IrfanView
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Grayscale vs. Color Color: pixel corresponds to three color intensities Red, Green, Blue In general, color image at least 3X footprint of grayscale
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RGB: Additive Color Model Start from no color present (black background) Add (emit) amounts of each primary Full intensity of each R,G,B: white Full intensity of R,G: yellow
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Resolution Image quality vs. number of pixels Each image below stretched to 200x200 pixels Fewer pixels less information stored 25x25 original 625 pixels 50x50 original 2500 pixels 100x100 original 10000 pixels
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Image Quality Vs. Color Levels Clockwise on right: 2 levels per R,G,B 4 levels per R,G,B 10 levels per R,G,B 40 levels per R,G,B More bits per pixel more colors larger footprint better quality
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