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🖼️ Digitising Images

🖼️ Converting Visual Information to Digital Form

Digitising images involves converting visual information from the real world into a digital format that computers can process, store, and display. Understanding this process is fundamental to working with digital images in information systems.

🔄 The Digitisation Process​

Converting an analog image to digital form involves two key steps:

1. 📊 Sampling​

  • Dividing the image into a grid of small squares called pixels (picture elements)
  • The number of pixels determines the resolution of the image
  • Higher resolution means more pixels and greater detail
  • Common resolutions include 1920×1080 (Full HD) and 3840×2160 (4K)

2. 🔢 Quantization​

  • Assigning a numerical value to each pixel to represent its color
  • The number of possible values depends on the bit depth
  • Higher bit depth allows more colors but requires more storage

📐 Resolution and Image Quality​

Resolution refers to the number of pixels in an image:

📏 Pixel Dimensions​

  • Expressed as width × height in pixels
  • Examples: 1280×720, 1920×1080, 3840×2160

🔍 Pixel Density​

  • Measured in pixels per inch (PPI) or dots per inch (DPI)
  • Determines how sharp an image appears at a given physical size
  • Higher PPI/DPI results in sharper images
  • Common values: 72 PPI for web, 300 DPI for printing

💡 Resolution Considerations​

  • Higher resolution captures more detail but requires more storage
  • Insufficient resolution results in pixelation when enlarged
  • Optimal resolution depends on the intended use (web, print, etc.)

🎨 Color Representation​

Digital images represent color using various models:

🎚️ Bit Depth​

  • Determines how many colors can be represented
  • 1-bit: 2 colors (black and white)
  • 8-bit: 256 colors or grayscale levels
  • 24-bit: Approximately 16.7 million colors (True Color)
  • 32-bit: 24-bit color plus 8-bit alpha channel for transparency

🌈 Color Models​

  • RGB (Red, Green, Blue): Additive color model used for displays
    • Each pixel has R, G, and B values (typically 0-255 each)
    • Example: (255, 0, 0) represents pure red
  • CMYK (Cyan, Magenta, Yellow, Key/Black): Subtractive model used for printing
  • HSV/HSL (Hue, Saturation, Value/Lightness): Alternative representations

📁 Image File Formats​

Different file formats store digitized images using various techniques:

📄 Uncompressed Formats​

  • BMP (Bitmap): Stores pixel data without compression
  • RAW: Contains minimally processed data from digital cameras

🗜️ Lossless Compression​

  • PNG (Portable Network Graphics): Supports transparency and lossless compression
  • GIF (Graphics Interchange Format): Limited to 256 colors, supports animation
  • TIFF (Tagged Image File Format): Flexible format used in publishing

📉 Lossy Compression​

  • JPEG (Joint Photographic Experts Group): Efficient compression for photographs
  • WebP: Modern format with better compression than JPEG

📦 Compression Techniques​

Image compression reduces file size for storage and transmission:

✅ Lossless Compression​

  • Reduces file size without losing any information
  • Original image can be perfectly reconstructed
  • Examples: Run-length encoding, dictionary-based methods
  • Typically achieves 2:1 to 3:1 compression ratios

📉 Lossy Compression​

  • Reduces file size by discarding some information
  • Original image cannot be perfectly reconstructed
  • Examples: Discrete Cosine Transform (used in JPEG)
  • Can achieve much higher compression ratios (10:1 to 100:1)
  • Quality vs. file size tradeoff

📷 Image Acquisition Devices​

Various devices are used to digitize images:

📸 Digital Cameras​

  • Use image sensors (CCD or CMOS) to capture light
  • Convert light into electrical signals, then digital values
  • Include smartphones, webcams, DSLRs, etc.

🖨️ Scanners​

  • Capture images from physical documents or photographs
  • Types include flatbed, document feeders, and specialized scanners
  • Resolution typically measured in DPI

🛠️ Image Processing​

After digitization, images can be processed in various ways:

🔧 Basic Operations​

  • Cropping, resizing, and rotating
  • Adjusting brightness, contrast, and color balance
  • Applying filters and effects

🧠 Advanced Processing​

  • Object recognition and feature extraction
  • Image enhancement and restoration
  • Compression and format conversion

🌟 Applications of Digital Images​

Digitized images are used in numerous applications:

  • 📸 Photography and visual arts
  • 🏥 Medical imaging (X-rays, MRIs, CT scans)
  • 🛰️ Satellite and aerial imaging
  • 📄 Document scanning and archiving
  • 👁️ Computer vision and machine learning
  • 🎮 Entertainment and gaming
  • 📱 Social media and communication

Understanding the principles of image digitization is essential for working with digital media and developing applications that process visual information.