Computer Vision Fundamentals of image formation Image Formats Color and Pixelation Digital image processing Types of images Convolution Neural Network Image Classification Image Segmentation Convolution Padding and Stride Object Detection YOLO Algorithm Computer Vision Quiz

Types of images

Images can be classified into various types based on their characteristics, content, and purposes.

Some common types of images:

  1. Binary Image: A binary image consists of only two colors, typically black and white (0 and 1). Each pixel is either completely black or completely white, representing foreground and background, respectively.

  2. Grayscale Image: A grayscale image contains shades of gray between black and white. Each pixel has a single intensity value that represents the brightness of that pixel.

  3. Color Image: Color images contain multiple color channels, often using the RGB (Red, Green, Blue) color model. Each pixel is represented by a combination of intensities in these color channels, allowing the representation of a wide range of colors.

  4. RGB Image: An RGB image is a type of color image that uses the RGB color model. It comprises three color channels: red, green, and blue. Each channel contributes to the final color of the pixel.

  5. CMYK Image: CMYK images are used for color printing. CMYK stands for Cyan, Magenta, Yellow, and Key (black). Unlike RGB, which is used for digital displays, CMYK is used for printing because it represents colors using subtractive color mixing.

  6. Multispectral Image: Multispectral images capture data in more than three spectral bands, such as infrared and ultraviolet. They are commonly used in remote sensing, agriculture, and geology to analyze specific characteristics of materials.

  7. Hyperspectral Image: Hyperspectral images capture data in many narrow and contiguous spectral bands. They are used for detailed material identification and analysis, often in fields like remote sensing and environmental monitoring.

  8. Depth Image: Depth images, also known as depth maps, represent the distance from the camera to each point in the scene. They are commonly used in 3D reconstruction and robotics.

  9. Segmented Image: A segmented image is one where different regions or objects in the image are labeled or outlined. Segmentation is often used for object detection and recognition.

  10. Panoramic Image: Panoramic images capture a wide field of view, often using stitching techniques to combine multiple images into a single large image.

  11. Satellite Image: Satellite images are captured by satellites orbiting the Earth and are commonly used in applications such as mapping, environmental monitoring, and urban planning.

  12. Medical Image: Medical images are used in the field of medicine for diagnostic purposes. They include X-rays, MRI scans, CT scans, and more.

  13. Artificially Generated Image: These images are generated by computer graphics techniques rather than being captured by cameras. They can be used in computer-generated imagery (CGI) for movies, video games, and simulations.

These are just a few examples of image types, and in practice, images can exhibit combinations of these characteristics. The type of image you encounter depends on the application and the technology used to capture or create the image.

Types of images


Enroll Now

  • Python Programming
  • Machine Learning