We may earn an affiliate commission when you visit our partners.

Raster Images

Save
May 1, 2024 3 minute read

Raster images, also known as bitmaps, are a fundamental concept in digital imaging and computer graphics. They are composed of a grid of individual pixels, each of which has a specific color and brightness value. Unlike vector images, which are defined mathematically and can be scaled indefinitely without loss of quality, raster images have a fixed resolution and will become pixelated if enlarged beyond their original size.

Understanding Raster Images

Raster images are commonly used in a wide range of applications, such as digital photography, web graphics, and print design. They are particularly well-suited for capturing realistic images with complex details and textures. However, due to their fixed resolution, they cannot be scaled up without losing image quality.

Advantages of Raster Images

Raster images offer several advantages over vector images:

  • Photographic Realism: Raster images can capture and reproduce photographic details and textures with high accuracy.
  • Simplicity: Raster images are relatively easy to understand and manipulate, especially for beginners.
  • Compatibility: Raster images are widely supported by most software and applications, making them accessible for a variety of uses.

Disadvantages of Raster Images

Raster images also have some limitations:

  • Fixed Resolution: Raster images cannot be scaled indefinitely without losing image quality.
  • File Size: Raster images can be large in file size, especially for high-resolution images.

Raster Image Formats

There are several common raster image formats, each with its own advantages and disadvantages:

Share

Help others find this page about Raster Images: by sharing it with your friends and followers:

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Raster Images.
Another comprehensive textbook on digital image processing, with a strong focus on image analysis and computer vision.
A textbook that covers a wide range of topics in computer vision, including image processing, feature extraction, and object recognition.
A book that covers the use of image and video compression techniques for multimedia applications.
A textbook that covers the use of image processing techniques in computer graphics, including topics such as image warping and morphing.
A practical guide to using the OpenCV library for computer vision tasks, with a focus on image processing and object detection.
A book that covers the use of image processing techniques in medical imaging, including topics such as image segmentation and registration.
A book that covers the use of image processing techniques for image forensics, such as image authentication and forgery detection.
A specialized book on digital halftoning, which is the process of converting continuous-tone images into binary images for printing.
Table of Contents
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser