Python Digital Image Processing From Ground Up™ (Udemy.com)
Image Processing : Edge-Detection Algorithms , Convolution, Filter Design, Gray-Level Transformation, Histograms etc.
Created by: Israel Gbati
Last updated September 2021
What you will learn
- Be able to suppress noise in images
- Be able to develop the 2-D Convolution algorithm in Python
- Apply Edge-Detection Operators like Laplacian, Sobel, Prewitt, Robinson etc. on Images
- Be able to develop Spatial Filtering Algorithms in Python
- Be able to compute an Image Histogram and Equalize it in Python
- Understand all about operators such as Laplacian, Sobel, Prewitt, Robinson etc.
- Be able to perform Image Processing using Python's Imaging Library
- Be able to perform Image Processing using SKImage
- Be able to perform Arithmetic and Boolean Operations like Addition, Subtraction, AND, OR etc. on images
- Be able to perform Image Enhancement Techniques such as Blurring and Sepia using Python
- Be able to give a lecture on Digital Image Processing
How it compares
Against the other 295 rated Udemy courses in Arduino on CourseDuck:
- Rating4.3 out of 5higher than 36% of them
- Reviews605#55 of 296 by number of reviews
- Length5 hoursshorter than 50% of them
- Last updatedSeptember 2021earlier than 70% of them
Course Description
With a programming based approach, this course is designed to give you a solid foundation in the most useful aspects of Image Processing in an engaging and easy to follow way. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories. To achieve this goal, the image processing techniques are explained in plain language, not simply proven to be true through mathematical derivations.
Still keeping it simple, this course comes in different programming languages so that students can put the techniques to practice using a programming language of their choice. This version of the course uses the Python programming language.
By the end of the course you should be able to perform 2-D Discrete Convolution with images in python, perform Edge-Detection in python , perform Spatial Filtering in python, compute an Image Histogram and Equalize it in python, perform Gray Level Transformations, suppress noise in images, understand all about operators such as Laplacian, Sobel, Prewitt, Robinson, even give a lecture on image processing and more. Please take a look at the full course curriculum.
REMEMBER : I have no doubt you will love this course. Also it comes with a FULL money back guarantee for 30 days! So put simply, you really have nothing to loose and everything to gain.
Sign up and lets start manipulating some pixels.
Instructor Details
- 4.3 Rating
605 Reviews
Israel Gbati
Author of Bare-Metal Embedded C Programming: Develop High-Performance Embedded Systems with C for Arm Microcontrollers.
With extensive experience in embedded firmware development, I specialize in real-time systems, low-level programming, medical device architecture, embedded signal processing, and embedded AI. My professional journey has been centered around Arm Cortex-Microcontrollers, delivering robust solutions used in cutting-edge industries.
Passionate about simplifying complex concepts.
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Reviews
By Luca Bortoloni on 5/13/2026
Il corso introduce bene alcuni concetti base di elaborazione delle immagini. Sarebbe stato opportuno usare caratteri dell’editor di una dimensione maggiore per una migliore leggibilità dei codici Python. Alcuni aspetti sono stati trattati un po’ velocemente. Nel complesso, sono comunque contento di aver seguito questo corso come introduzione all’argomento.
By Tanausu Ramirez on 11/14/2022
As a practical course it's ok, although It can be improved explaining more specific uses of each filter and technique or using more practical real cases. Also, I don't understant the section 12 about Raspberri Py while some content seems missong or not covered like "Be able to perform Image Enhancement Techniques such as Blurring and Sepia using Python".
By Vartika Agarwal on 7/9/2021
This course was very useful as a beginner. In-depth learning experience in simple language
By José Lema C on 6/23/2020
muy clara la explicación de como importar las librerias y como instalar python, lo intenté por mi cuenta sin exito aparente, pero acá ya me quedaron claras varias cosas. los conceptos básicos para empezar a abordar el tema del procesamiento de imágenes ha sido muy bueno. PERO los videos de aplicación especialmente al final, están desactualizados, la versión actual de Python no tiene unos comandos que se utilizaron en esta clase por lo tanto no todo es aplicable. y otro pero que noté es que hay comentarios de hace mas de 3 meses que no han respondido, por lo tanto es un poco decepcionante al final. La teoria es buena, muy básica, pero asi lo prometieron.
By Anonymized User on 4/26/2020
Yes, it's very good in general so far. The only challenge is that sometimes it's tricky to translate the setup instructions from windows to my Mac. I haven't gotten completely stuck, but it took me a while to figure some of that out. Separate instructions for Mac would have been very helpful and allowed me to spend more time on what I actually want to learn.
By Ritwik Saha on 4/7/2020
It was a great match for me. I have started working on my own image processing project after completing my training. Many thanks to the trainer.
By Iniyavel S on 1/31/2020
The instructor packs all the necessary information in the shortest possible time. I paused all the videos and took notes in order to retain all the information. This will certainly come in handy when I look for a job. This course is very valuable. Thank you very much Mr. Israel Gbati. -I.
By Gaurav Verma on 10/1/2019
Its good going till now. I wish if the codes were displayed without using the inbuilt libraries function.
By Mohit Jagdale on 7/2/2019
Its a nice preliminary course. The only thing I will recommend is that the syntax used in each program could have been explained in more detail.
By Alex He on 4/3/2019
It was a good match. I am very new to image processing and I was looking for a course that takes it from the ground up. I would like to see more "in depth" on the equations as well more examples during the theory-part. Maybe show an picture of each stage in a explanation.
Quality Score
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Overall Score : 86 / 100












