Data Representation of Images
A digital image is made of tiny coloured squares called pixels, and each pixel has a binary colour value.
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A digital image is made of tiny coloured squares called pixels, and each pixel has a binary colour value.
- More pixels means higher resolution
- Colour depth is bits per pixel
- File size grows with both
🧠 Quick quiz
Three questions. Score 2 or more to complete the topic.
What is Data Representation of Images?
Within Computer Science, which covers algorithms, programming, data, networks, hardware and safe, responsible use of technology, this topic explains Data Representation of Images. Computing topics explain how software, hardware and data work, with diagrams and models that show each step in order.
Check that you can explain Data Representation of Images in your own words and give one example from everyday life. If you can do that, you have understood the core idea.
Understanding Data Representation of Images helps you design, test and explain programs, websites and systems, from small projects to exam questions.
Data Representation of Images in detail
Digital images are made of pixels (picture elements), each stored as a binary number for its colour. Bitmap images have a grid of pixels, with resolution (number of pixels) and colour depth (bits per pixel) deciding quality and size. One bit per pixel gives black and white, 8 bits gives 256 colours and 24 bits gives about 16.7 million (RGB).
File size = width × height × colour depth. Higher resolution gives more detail but a larger file, and compression can reduce it. Vector graphics store shapes as mathematical descriptions, so they scale without loss of quality. Metadata stores extra information such as the date and camera.
How the interactive helps you understand Data Representation of Images
Watch the binary display in the interactive. Use any sliders or buttons it offers to change the values and see how the binary display responds.
Before you change anything, predict the result. Then change one value at a time and check whether your prediction was right. This is a quick way to build a correct mental model of Data Representation of Images.
Real-life uses and examples
- Explain Data Representation of Images to someone new to computing by comparing it to a familiar process.
- Trace through a process that uses Data Representation of Images to check what it does step by step.
- Recognise Data Representation of Images in an app or device you use every day.
Common mistakes to avoid
- Using the term without being able to say what the computer actually does.
- Testing only the normal case and forgetting the edge cases.
- Learning the definition without testing it. Use the quiz and the interactive to check that you can apply the idea.
Frequently asked questions about Data Representation of Images
What is Data Representation of Images?
A digital image is made of tiny coloured squares called pixels, and each pixel has a binary colour value.
What are the most important points about Data Representation of Images?
The main points are: More pixels means higher resolution; Colour depth is bits per pixel; File size grows with both.
Why is Data Representation of Images useful?
Understanding Data Representation of Images helps you design, test and explain programs, websites and systems, from small projects to exam questions.
How can I practise Data Representation of Images?
Open the interactive at the top of this page and change the controls one at a time. Predict the result before each change, then take the three-question quiz. A score of two or more marks the topic as complete on this device.
Which topics are related to Data Representation of Images?
Related topics in Computer Science include Computer History, Graphics and Animation, User Interface Design.