Coursera

Camera and Imaging (Coursera)

Offered by Columbia University,

This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or processing by a human or a machine. Imaging has a long history, spanning several centuries. But the advances made in the last three decades have revolutionized the camera and dramatically improved the robustness and accuracy of computer vision systems. We describe the fundamentals of imaging, as well as recent innovations in imaging that have had a profound impact on computer vision.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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).

What You Will 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

Course 1 of 5 in the First Principles of Computer Vision Specialization

Syllabus

WEEK 1: Getting Started: Camera and Imaging
WEEK 2: Image Formation
WEEK 3: Image Sensing
WEEK 4: Binary Images
WEEK 5: Image Processing I
WEEK 6: Image Processing II

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

Edge Impulse

Computer Vision with Embedded Machine Learning (Coursera)

Data Science

Computer vision (CV) is a fascinating field of study that attempts to automate the process of assigning meaning to digital images or videos. In other words, we are helping computers see and understand the world around us! A number of machine learning (ML) algorithms and techniques can be used to accomplish CV tasks, and as ML becomes faster and more efficient, we can deploy these techniques to embedded systems.

Aug 31st 2026

3 Weeks

Machine Learning Computer Vision Object Detection

Coursera

DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

CS: Software Engineering Computer Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Sep 14th 2026

4 Weeks

Artificial Intelligence Machine Learning Neural Networks

Coursera

Arizona State University

Introduction to Machine Learning with Python (Coursera)

CS: Software Engineering CS: Programming

This course will give you an introduction to machine learning with the Python programming language. You will learn about supervised learning, unsupervised learning, deep learning, image processing, and generative adversarial networks. You will implement machine learning models using Python and will learn about the many applications of machine learning used in industry today. You will also learn about and use different machine learning algorithms to create your models.

Sep 7th 2026

4 Weeks

Python Machine Learning Image Processing

Coursera

Coursera Project Network

Object Localization with TensorFlow (Coursera)

Data Science

Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs.

Aug 31st 2026

Self-Paced

Machine Learning Computer Vision Data Visualization

Coursera

University of London,Royal Holloway, University of London

Film, Images & Historical Interpretation in the 20th Century: The Camera Never Lies (Coursera)

Humanities

This course is a short taster on the topic of the use of Images, Film, and their use in historical interpretation in the 20th century. It is primarily provided for those who have a general interest in history that draws on photojournalism as primary evidence, and films based on historical events.

Sep 7th 2026

5-12 Weeks

Image History Film

Coursera

MathWorks

Automating Image Processing (Coursera)

CS: Software Engineering

In this course, you will build on the skills acquired in Image Segmentation, Filtering, and Region Analysis to explore large sets of images and video files. It’s impractical to manually inspect results in large data sets. Automating image processing allows you to do your work more efficiently.

Aug 31st 2026

4 Weeks

MATLAB Video Processing Image Processing

Coursera

Johns Hopkins University

Introduction to Neurohacking In R (Coursera)

Statistics & Data Analysis Data Science

Neurohacking describes how to use the R programming language and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization.

Sep 7th 2026

4 Weeks

Brain Neurology R Language

Coursera

Michigan State University

Cameras, Exposure, and Photography (Coursera)

Architecture & Design

Welcome to Course One of Photography Basics and Beyond: From Smartphone to DSLR! In these first 4 Modules you will gain the knowledge and the confidence that will help you make good choices as you consider qualities of the camera you own, and the qualities of the other types of digital cameras you might be considering. You will learn about the basic functions that most digital cameras have in common. You will also go beyond the "technical" matters and learn about how you can make exciting pictures by emphasizing the aspects of Frame and Vantage Point to interpret old subjects in new ways.

Sep 7th 2026

4 Weeks

Photography Creativity Exposure

Coursera

The Museum of Modern Art

Seeing Through Photographs (Coursera)

Film & Audio

Although taking, sharing, and viewing photographs has become second nature for many of us, our regular engagement with images does not necessarily make us visually literate. This course aims to address the gap between seeing and truly understanding photographs by introducing a diversity of ideas, approaches, and technologies that inform their making. In this course you will look closely at 100 photographs from the collection of The Museum of Modern Art, going behind the scenes of the Museum and into artist studios through original films and audio interviews.

Sep 21st 2026

5-12 Weeks

Image History Photography

Coursera

Yale University

Visualizing the Living Body: Diagnostic Imaging (Coursera)

Health & Society

This course teaches learners the underlying principles behind conventional radiography, computerized axial tomography (CT), magnetic resonance imaging (MRI), and ultrasound. The radiology of chest, abdomen, pelvis, extremities, spine and brain are taught in this course using a combination of lectures and extensive practical activities and assessments.

Sep 7th 2026

5-12 Weeks

Anatomy Human Anatomy Magnetic Resonance Imaging

Coursera

Coursera Project Network

Landing.AI for Beginners: Build Data Visualization AI Models (Coursera)

Data Science

In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.

Sep 21st 2026

1 Week

Artificial Intelligence Computer Vision Data Visualization

Coursera

Columbia University

Visual Perception (Coursera)

Computer Science

The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The first is the separation of an image into object and background using a technique called change detection.

Sep 7th 2026

5-12 Weeks

Neural Networks Computer Vision Visual Perception