Camera and Imaging

This course is part of First Principles of Computer Vision Specialization

Instructor: Shree Nayar

What you'll learn

  •   Learn how a camera works and how an image is formed using a lens
  •   Understand how an image sensor works and its key characteristics
  •   Design cameras that capture high dynamic range and wide angle images
  •   Learn to create binary images and use them to build a simple object recognition system
  • Skills you'll gain

  •   Algorithms
  •   Linear Algebra
  •   Computer Vision
  •   Image Analysis
  •   Visualization (Computer Graphics)
  •   Computer Graphics
  •   Electronic Components
  •   Advanced Mathematics
  •   Semiconductors
  •   Color Theory
  •   Photography
  • There are 6 modules in this course

    This course starts with examining how an image is formed using a lens camera. We explore the optical characteristics of a camera such as its magnification, F-number, depth of field and field of view. Next, we describe how solid-state image sensors (CCD and CMOS) record images, and the key properties of an image sensor such as its resolution, noise characteristics and dynamic range. We describe how image sensors can be used to sense color as well as capture images with high dynamic range. In certain structured environments, an image can be thresholded to produce a binary image from which various geometric properties of objects can be computed and used for recognizing and locating objects. Finally, we present the fundamentals of image processing – the development of computational tools to process a captured image to make it cleaner (denoising, deblurring, etc.) and easier for computer vision systems to analyze (linear and non-linear image filtering methods).

    Image Formation

    Image Sensing

    Binary Images

    Image Processing I

    Image Processing II

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