Data Representation: Storing Images

Introduction to Image Data

An image consists of a collection of pixels, each with their own coordinates and colour.
Each pixel in an image is represented by a binary code, which will determine the colour and intensity of that pixel.
The more pixels an image has, the higher the resolution – a high-resolution image conveys more visual information than low-resolution images, but at a higher data cost.

Bitmap images, also known as raster images, are composed of pixels in a grid.
Each pixel is represented by colour depth, the number of bits used to store colour data for each pixel. More bits provide a wider range of possible colours.
Common bitmap image formats include .jpeg, .png, and .bmp.
Bitmap images can lose quality when zoomed in or resized due to the fixed number of pixels.

Vector images are not composed of pixels. Instead, they use mathematical formulas to draw lines and curves that make up the image.
This means that vector images can be resized without any loss in quality, unlike bitmap images.
Common vector image formats include .svg and .ai.

Various methods are used to reduce the amount of data needed to store image data.
Lossy compression reduces file size by throwing away less significant data. Once lost, this data cannot be recovered, which can cause loss of quality.
Lossless compression reduces file size without losing data, preserving the original quality of the image. However, this method does not reduce file size as drastically as lossy compression.
Images are also optimised by changing the image size, reducing the resolution or altering the colour depth.

Different file formats use different methods of compression, resulting in variations in file size and image quality.
Metadata about an image (such as its dimensions, colour depth, or the date it was created) is also stored in the file.

Colour depth refers to the number of bits used to represent the color of each pixel in an image. The greater the colour depth, the more colours can be represented.
1 bit colour depth can represent 2 different colours (usually black and white), while 24 bit colour depth can represent around 16.7 million colours.
Increasing the colour depth results in higher quality images, but also increases file size.