Text, Sound And Images (Copy)

Representation of Text

• Why computers represent text in binary
  • Computers process and store all data in binary form (0s and 1s).
  • Every character (letter, number, punctuation, symbol) is assigned a unique binary code through a character set.
  • Character sets map characters to numeric codes which can be converted to binary for processing.

Character Sets

• ASCII (American Standard Code for Information Interchange)
  • 7-bit ASCII:
    • Can represent 2⁷ = 128 characters.
    • Includes:
      • Uppercase letters (A–Z)
      • Lowercase letters (a–z)
      • Digits (0–9)
      • Basic punctuation
      • Control characters (e.g., carriage return, line feed).
    • Example:
      • ‘A’ = 65₁₀ → 1000001₂
      • ‘a’ = 97₁₀ → 1100001₂
  • 8-bit Extended ASCII:
    • Uses 8 bits → 2⁸ = 256 characters.
    • Adds extra symbols, graphical characters, and accented letters.
• Unicode
  • Designed to represent characters from all writing systems (e.g., Latin, Greek, Arabic, Chinese, Hindi, emoji).
  • Uses variable lengths:
    • UTF-8 (1–4 bytes per character)
    • UTF-16 (2 or 4 bytes per character)
    • UTF-32 (4 bytes per character)
  • Allows over a million unique characters.
  • Example:
    • ‘A’ = U+0041 in Unicode.
    • Emoji 😀 = U+1F600 in Unicode.
• Comparison: ASCII vs Unicode
  

  Feature	ASCII	Unicode
  Characters	128 or 256	1.1 million+
  Bits per char	7 or 8	Variable (8–32 bits)
  Language scope	English + limited symbols	All languages, symbols, emoji

Representation of Sound

• How sound is converted to binary
  • Sound is a continuous analogue wave in the real world.
  • A microphone detects sound waves and converts them to analogue electrical signals.
  • An Analogue-to-Digital Converter (ADC) samples the sound at regular intervals and converts each sample into binary.
  • Sampling: Measuring the amplitude (loudness) of the sound wave at fixed time intervals.

Sample Rate

• The number of samples taken per second, measured in Hertz (Hz).
• Common values:
  • 8,000 Hz – Telephone quality
  • 44,100 Hz – CD quality
  • 48,000 Hz – Professional audio
• Higher sample rate → closer to original sound, better quality, but larger file size.

Sample Resolution

• Number of bits per sample.
• Determines the precision of each measurement of amplitude.
• Example:
  • 8-bit resolution: 2⁸ = 256 possible amplitude levels.
  • 16-bit resolution: 2¹⁶ = 65,536 possible amplitude levels.
• Higher resolution → more accurate sound representation → larger file size.

File size for digital audio

• Formula:
  File size (bits) = Sample rate × Sample resolution × Duration (seconds) × Number of channels
• Example:
  • Stereo recording (2 channels)
  • 44,100 Hz sample rate
  • 16-bit resolution
  • 60 seconds duration:
  • File size = 44,100 × 16 × 60 × 2 = 84,672,000 bits ≈ 10.08 MB.

Representation of Images

• Pixels:
  • Short for “picture elements”.
  • Smallest unit of an image, each with a colour value.
  • An image is a grid of pixels stored in binary.

Resolution

• Number of pixels in an image.
• Expressed as:
  • Width × Height (e.g., 1920×1080 pixels)
  • Total pixel count.
• Higher resolution → more detail → larger file size.

Colour Depth

• Number of bits used to represent each pixel’s colour.
• Determines the number of possible colours:
  • 1-bit colour depth: 2 colours (black & white)
  • 8-bit colour depth: 256 colours
  • 24-bit colour depth: 16.7 million colours (true colour)
• Formula for possible colours: 2^(colour depth).

File size for digital images

• Formula:
  File size (bits) = Resolution (total pixels) × Colour depth
• Example:
  • 1920×1080 pixels
  • 24-bit colour depth:
  • File size = 1920 × 1080 × 24 = 49,766,400 bits ≈ 5.94 MB.

Impact on Quality and Storage