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Understanding Conventional and Digital Cameras: From Chemical Processes to Digital Imaging

This lecture explores the workings of conventional and digital cameras, comparing their mechanisms. Conventional cameras utilize chemical and mechanical processes, with film that reacts to light to create a chemical record. In contrast, digital cameras use sensors to convert light into electrical charges, creating images through analog-to-digital conversion. We discuss the differences in capturing color, the significance of grayscale versus color images, and the impact of pixel resolution on image quality and storage. Understanding these elements is crucial for grasping digital image processing.

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Understanding Conventional and Digital Cameras: From Chemical Processes to Digital Imaging

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Presentation Transcript

  1. Digital Image processing CMSC 150: Lecture 14

  2. 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

  3. Conventional Cameras

  4. 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

  5. Analog to Digital Conversion: Sampling

  6. Analog to Digital Conversion: Sampling

  7. Analog to Digital Conversion: Sampling

  8. Analog to Digital Conversion: Sampling

  9. Analog to Digital Conversion: Sampling

  10. Digital Image • Sensor: 2D array of values • Image: "value" stored for cell in the sensor • Pixel: picture element • One pixel per sensor cell

  11. Capturing Color • Color filter placed over sensor • Color at each cell determined as "average of neighbor cells" (How Stuff Works animation)

  12. Grayscale vs. Color • Grayscale: pixel corresponds to shade of gray • Highest value: white • Lowest value: black

  13. 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

  14. Grayscale vs. Color • Color: pixel corresponds to three color intensities • Red, Green, Blue • In general, color image at least 3X footprint of grayscale

  15. 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

  16. 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

  17. 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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