data representation definition computing

5. Data Representation

Introduction

Computers are machines that do stuff with information. They let you view, listen, create, and edit information in documents, images, videos, sound, spreadsheets and databases. They let you play games in simulated worlds that don’t really exist except as information inside the computer’s memory and displayed on the screen. They let you compute and calculate with numerical information; they let you send and receive information over networks. Fundamental to all of this is that the computer has to represent that information in some way inside the computer’s memory, as well as storing it on disk or sending it over a network.

Chapter sections

5.1. What's the big picture?
5.2. Getting started
5.3. Numbers
5.5. Images and Colours
5.6. Program Instructions
5.7. The whole story!
5.8. Further reading

All Subjects

Computer Vision and Image Processing

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Data representation refers to the way in which information is encoded, stored, and presented in a format that can be understood and processed by computers and human users. It encompasses various methods, including numerical, textual, graphical, and auditory formats, that transform raw data into a meaningful form for analysis or visualization. The effectiveness of data representation greatly influences how well information can be communicated and understood.

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5 Must Know Facts For Your Next Test

Data representation is crucial in computer vision as it determines how images are interpreted and processed by algorithms.
Different forms of data representation, such as 2D versus 3D representations, can significantly affect the analysis and outcomes in image processing tasks.
Visual data representation techniques, like histograms or heatmaps, help convey complex information effectively and are widely used in computational displays.
Standard formats for data representation include JPEG for images, which compresses data to save space while maintaining quality.
Choosing the right data representation can enhance computational efficiency, leading to faster processing times in applications like real-time image recognition.

Review Questions

Data representation plays a key role in determining how efficiently image processing algorithms operate. Different representations can lead to variations in computational complexity; for instance, using a lower bit depth may reduce the amount of data to process but can also limit color accuracy. By selecting an appropriate data representation method that aligns with the algorithm's requirements, developers can enhance processing speed and overall system performance.
Different types of data representations—such as pixel-based images versus vector graphics—affect how visual information is interpreted by both humans and machines. Pixel-based images are composed of discrete elements that may lose detail when scaled up, while vector graphics maintain clarity regardless of size due to their mathematical basis. This distinction impacts usability in applications like computer graphics and augmented reality where clarity and scalability are vital.
Effective data representation techniques are crucial for enhancing user interaction with computational displays by making complex information accessible and understandable. Techniques such as interactive visualizations or well-structured graphical user interfaces allow users to engage with data intuitively. For example, utilizing dynamic charts and responsive designs can significantly improve user experience by providing immediate feedback and clearer insights into underlying patterns or trends within the data.