Bitmap Image Size and Colour Depth (AQA GCSE Computer Science): Revision Notes

Bitmap image size and colour depth

What is a bitmap image?

A bitmap image is made up of tiny squares called pixels. Each pixel can display a different colour, and when you put thousands of these pixels together, they create the complete image you see on screen.

The simple cat drawing shown above helps us understand how bitmap images work. Even this basic image is made up of many individual pixels arranged in rows and columns.

Understanding image size

The image size of a bitmap tells us how many pixels wide and how many pixels tall the image is. We always measure this as width × height in pixels.

For example:

• A small image might be 100 × 150 pixels (100 pixels wide, 150 pixels tall)
• A larger image could be 1920 × 1080 pixels (common for HD displays)

Calculating total pixels

To find out how many pixels are in an image, you multiply the width by the height:

$\text{Total pixels} = \text{width} \times \text{height}$

What is resolution?

Resolution refers to how many pixels are packed into a given physical space. A higher resolution image has more pixels crammed into the same area, which means:

• The image appears sharper and more detailed
• More data is needed to store the image
• The file size becomes larger

Understanding colour depth

Colour depth (also called bit depth) tells us how many different colours each pixel can display. This depends on how many bits of data we use to store each pixel's colour information.

How bits determine colours

The number of possible colours follows a simple rule:

$\text{Number of colours} = 2^{\text{number of bits}}$

Here's how it works:

• 1 bit per pixel: $2^1 = 2$ colours (usually black and white)
• 2 bits per pixel: $2^2 = 4$ colours
• 3 bits per pixel: $2^3 = 8$ colours
• 8 bits per pixel: $2^8 = :highlight[256 colours]$
• 16 bits per pixel: $2^{16} = :highlight[65,536 colours]$

Binary representation of colours

When we use 2 bits per pixel to create 4 different colours, we might assign:

• 00 = white
• 01 = red
• 10 = green
• 11 = black

The relationship between colour depth and file size

Real-world example

These images demonstrate how reducing colour depth affects both image quality and file size. The original image with 256 colours (8-bit depth) was 1.2 MB in size. When reduced to just 8 colours, the file size dropped to 787 KB, and with only 4 colours, it became just 542 KB.

Calculating file size

To work out how much storage space a bitmap image needs:

1. Find total pixels: width × height
2. Multiply by bits per pixel: total pixels × colour depth (in bits)
3. Convert to bytes: divide by 8 (since 8 bits = 1 byte)

$\text{File size} = \frac{\text{width} \times \text{height} \times \text{colour depth}}{8} \text{ bytes}$

Practical considerations

When working with bitmap images, you need to balance three factors:

• Image quality: Higher colour depth gives better quality
• File size: More colours create larger files
• Storage/bandwidth: Larger files take more space and longer to transfer

For different purposes, you might choose different colour depths:

• Web graphics: Often 8-bit (256 colours) for smaller file sizes
• Professional photography: 16-bit or higher for maximum quality
• Simple graphics: 4-bit or less for very small files