C2 · Text and Image Representation

Spec reference: Sections C2 and C3 - How Data is Represented Key idea: Understand how text is encoded using character sets and how images are stored as binary data.

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Text representation

Character sets

A character set is a mapping between characters (letters, numbers, symbols) and binary codes. Every character stored on a computer has a unique binary number assigned to it.

ASCII

ASCII (American Standard Code for Information Interchange) uses 7 bits, giving 128 possible characters (0-127).

Range	Characters
0-31	Control characters (non-printable, e.g. newline)
32-126	Printable characters (letters, digits, symbols)
65-90	Uppercase A-Z
97-122	Lowercase a-z
48-57	Digits 0-9

Extended ASCII uses 8 bits (256 characters) and adds accented characters and symbols.

Limitation: ASCII only supports English and a few Western European characters. It cannot represent Chinese, Arabic, emoji, or most world languages.

Unicode

Unicode was designed to represent every character in every language.

Standard	Bits	Characters supported
UTF-8	Variable (1-4 bytes)	Over 1.1 million code points
UTF-16	2 or 4 bytes	Same range as UTF-8
UTF-32	4 bytes fixed	Same range

UTF-8 is backward compatible with ASCII: the first 128 Unicode code points are identical to ASCII. This is why UTF-8 is the dominant encoding on the web.

Implications of Unicode:

• Files are larger than ASCII because characters can use more bytes.
• Universal: one standard supports all world languages, emoji, and special symbols.
• Ensures text displays correctly when shared across different systems and countries.

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Image representation

How bitmap/raster images are stored

A bitmap image is a grid of pixels. Each pixel stores a colour value as a binary number.

Key terms:

Term	Definition
Pixel	The smallest individual element in a bitmap image
Resolution	The number of pixels in the image (width x height), e.g. 1920x1080
Bit depth (colour depth)	Number of bits used to represent the colour of each pixel

Bit depth and colour

Bit depth	Colours available	Notes
1 bit	2 (black and white)	Minimal storage
8 bit	256	Greyscale or limited colour
24 bit	16,777,216 (true colour)	Red, Green, Blue - 8 bits each
32 bit	True colour + transparency	24-bit RGB plus an 8-bit alpha channel

Calculating file size

$$\text{File size (bits)}=\text{image width}\times \text{image height}\times \text{bit depth}$$

Example: A 100 x 100 pixel image with 24-bit colour depth:

• $100\times 100\times 24=240,000$ bits = 30,000 bytes = approximately 29.3 KB

Impact of resolution

Higher resolution means more pixels, which means:

• Greater detail and clarity.
• Larger file size.
• More processing power needed to display or edit.

Impact of bit depth

Higher bit depth means more colours per pixel, which means:

• More realistic colour representation.
• Larger file size.

Compression

Because bitmap images can be very large, compression is used to reduce file size.

Type	Description	Quality	File formats
Lossless	Removes redundant data without losing any quality. The original can be perfectly restored.	No quality loss	PNG, BMP, GIF
Lossy	Permanently removes some data to achieve much smaller file sizes. Quality degrades.	Some quality loss	JPEG

Exam point

Always state that lossy compression cannot be reversed. Once data is discarded, the original cannot be restored. Lossless compression can always be perfectly decompressed.

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Summary

Term	Meaning
ASCII	7-bit character encoding supporting 128 characters
Unicode (UTF-8)	Universal variable-width encoding supporting all world languages
Pixel	The smallest element of a bitmap image
Bit depth	Number of bits used per pixel to represent colour
Lossless compression	Reduces file size with no quality loss
Lossy compression	Reduces file size by permanently discarding data

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