Coursera

Introduction to Image Processing (Coursera)

Offered by MathWorks,
Introduction to Image Processing (Coursera)

In this introduction to image processing, you'll take your first steps in accessing and adjusting digital images for analysis and processing. You will load, save, and adjust image size and orientation while also understanding how digital images are recognized. You will then perform basic segmentation and quantitative analysis. Lastly, you will enhance the contrast of images to make objects of interest easier to identify.

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

By the end of the course, you’ll apply your segmentation skills to identify regions of interest, such as the amount of surface water from satellite images. This introduction to image processing will give you the foundation you need to conduct more advanced work on this topic.
You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science and provides the capabilities you need to accomplish your image processing tasks. You will be provided with free access to MATLAB for the duration of the course to complete your work.
To be successful in this course you should have a background in basic math and some exposure to MATLAB. If you want to familiarize yourself with MATLAB check out the free, two-hour MATLAB Onramp. Experience with image processing is not required.
Course 1 of 3 in the Image Processing for Engineering and Science Specialization.

Syllabus

WEEK 1: Introduction to Digital Images
WEEK 2: Working with Image Data
WEEK 3: Thresholding Images
WEEK 4: Adjusting Image Contrast

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

Related Courses

Data Analysis and Visualization (Coursera) Coursera
University at Buffalo,The State University of New York

Data Analysis and Visualization (Coursera)

Business

By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story.

Jun 8th 2026
4 Weeks
Python MATLAB Software
Details
Mathematics for Engineers: The Capstone Course (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Mathematics for Engineers: The Capstone Course (Coursera)

Sci: Mathematics

Mathematics for Engineers: The Capstone Course provides a capstone project for students who are completing the Mathematics for Engineers specialization. Students will first learn some basic concepts in computational fluid dynamics, and then apply these concepts to compute the fluid flow around a cylinder. Access to MATLAB online and the MATLAB grader is given to all students who enroll.

Jun 15th 2026
3 Weeks
Math MATLAB Fluid Flow
Details
Principles of Photo Composition and Digital Image Post-Production (Coursera) Coursera
Michigan State University

Principles of Photo Composition and Digital Image Post-Production (Coursera)

Film & Audio

Welcome to Course THREE! In the first two Modules you will gain a more professional-level understanding of the Design Elements that artists have used throughout history to create successful compositions. Arranging the Elements in ways that lead viewers through their compositions is an essential craft for photographers no matter whether their subject matter is pure documentary or vividly exotic personal expression.

Jun 8th 2026
4 Weeks
Photography Composition Digital Image
Details
Visual Perception (Coursera) 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.

Jun 15th 2026
5-12 Weeks
Neural Networks Computer Vision Visual Perception
Details
Introdução ao Controle Moderno (Coursera) Coursera
Instituto Tecnológico de Aeronáutica

Introdução ao Controle Moderno (Coursera)

Engineering Sci: Physics

Este curso lhe dará a base necessária para entender técnicas mais avançadas de controle moderno. Você aprenderá como representar a dinâmica de um sistema no espaço de estados, como analisar um sistema no espaço de estados, como projetar uma realimentação de estado e como projetar um observador de estado.

Jun 1st 2026
5-12 Weeks
MATLAB Modeling Electrical Engineering
Details
Machine Learning for Computer Vision (Coursera) Coursera
MathWorks

Machine Learning for Computer Vision (Coursera)

Data Science

In the second course of the Computer Vision for Engineering and Science specialization, you will perform two of the most common computer vision tasks: classifying images and detecting objects. You will apply the entire machine learning workflow, from preparing your data to evaluating your results. By the end of this course, you’ll train machine learning models to classify images of street signs and detect material defects.

Jun 15th 2026
4 Weeks
MATLAB Machine Learning Computer Vision
Details
Controle de Sistemas no Plano-s (Coursera) Coursera
Instituto Tecnológico de Aeronáutica

Controle de Sistemas no Plano-s (Coursera)

Engineering

Após esse curso você será capaz de esboçar o Lugar Geométrico das Raízes (LGR - Root Locus) do denominador da Função de Transferência em Malha Fechada a partir dos polos e zeros da Função de Transferência em Malha aberta. Você também será capaz de projetar controladores de avanço de fase para atender simultaneamente requisitos de desempenho de amortecimento e de velocidade da resposta.

Jun 8th 2026
5-12 Weeks
MATLAB Engineering Simulation
Details
Predictive Modeling and Machine Learning with MATLAB (Coursera) Coursera
MathWorks

Predictive Modeling and Machine Learning with MATLAB (Coursera)

Data Science

In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background.

Jun 8th 2026
4 Weeks
ML MATLAB Machine Learning
Details
Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera) Coursera
Duke University

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera)

Engineering Sci: Mathematics

In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space.

Jun 15th 2026
5-12 Weeks
Math Image Video
Details
Object Tracking and Motion Detection with Computer Vision (Coursera) Coursera
MathWorks

Object Tracking and Motion Detection with Computer Vision (Coursera)

Engineering

In the third and final course of the Computer Vision for Engineering and Science specialization, you will learn to track objects and detect motion in videos. Tracking objects and detecting motion are difficult tasks but are required for applications as varied as microbiology and autonomous systems. To track objects, you first need to detect them. You’ll use pre-trained deep neural networks to perform object detection. You’ll also use optical flow to detect motion and use the results to detect moving objects.

Jun 15th 2026
4 Weeks
MATLAB Computer Vision Object Detection
Details