Describe how bitmap images are represented using pixels and colour depth, and explain how resolution and colour depth affect image quality and file size.

What this dot point is asking

WJEC asks you to explain how a digital photograph or graphic is stored as binary, and how two key settings, resolution and colour depth, control both how good the image looks and how big the file is. This is one of the most common calculation questions in Unit 1, so you must be able to define the terms and work out a file size from them.

Pixels and bitmaps

A digital image of the bitmap type is divided into a rectangular grid of small dots.

Zoom far enough into a bitmap and you see the individual coloured squares. The image is rebuilt on screen by colouring each pixel according to its stored binary value.

Resolution

Resolution describes how many pixels make up the image.

A low-resolution image has few pixels and looks blocky or pixelated when enlarged, because each pixel is stretched. A high-resolution image has many pixels and stays sharp, at the cost of a larger file.

Colour depth

Colour depth controls how many different colours each pixel can be.

More bits per pixel means a wider range of colours and smoother shading, improving quality, but it increases the number of bits in the file.

Calculating image file size

This is the headline exam skill for this dot point.

Metadata

Real image files also store extra information beyond the pixel data.

In exam calculations you are usually told to ignore metadata, but you should know it exists and that it adds slightly to the real file size.

Resolution and colour depth together

The two settings affect quality and size in different ways, and a strong answer keeps them distinct. Resolution decides how many points of detail there are, so a higher resolution captures finer shapes and edges and stays sharp when enlarged. Colour depth decides how many colours each of those points can be, so a higher colour depth captures subtle shading and smooth gradients without visible banding. Both multiply into the size formula, so increasing either raises the file size: doubling the colour depth doubles the data, and doubling both dimensions of the resolution quadruples it. When a question asks you to reduce a file size, you can therefore suggest lowering the resolution, lowering the colour depth, or both, and explain the quality cost of each.

Vector graphics as a contrast

The images in this dot point are bitmaps, made of a grid of pixels, but it helps to know that some graphics are stored differently. A vector graphic stores a set of instructions and shapes (lines, curves, fills) rather than individual pixels, so it can be scaled to any size without becoming blocky and often has a smaller file size for simple images such as logos. Bitmaps suit photographs, where every pixel may differ, while vectors suit flat, geometric artwork. The exam focus here is bitmap representation and its file-size calculation, but recognising why a logo might be a vector while a photo is a bitmap shows a fuller understanding of how images are stored.

Why this matters

Image size calculations connect directly to storage and compression: a high-resolution, high-colour-depth photo can be several megabytes, which is why images are often compressed before being sent or stored. Understanding the trade-off between quality and file size lets you justify why a photographer might keep large files while a website uses smaller, lower-resolution versions to load quickly.