
Discover how to learn effectively in this MATLAB image processing course by engaging with code, pausing to recreate a gui in MATLAB's Guide tool, and mastering variables, loops, and functions.
Learn to use MATLAB's get and set to access and modify properties of figures, axes, and plots via handles, adjusting limits, fonts, colors, line width, and markers.
Learn to create and customize Matlab gui using guide, build a blank interface, add axes, text, and a button, and plot random lines with callbacks.
Implement calculator buttons in MATLAB GUIs, adding plus, minus, divide, and multiply with a loop; include equals and clear, a text display, and align and color the UI.
Define the MATLAB GUI button functions to capture presses, flash the button, and update the calculator display text. Build expressions from presses, evaluate on equals, and implement clear.
Learn to import and display pictures in MATLAB with a file picker GUI that filters jpeg and png files, then load and view images using imread and imshow.
Learn to smooth images with a two dimensional gaussian kernel in MATLAB by constructing and normalizing the Gaussian, then applying convolution across RGB channels while preserving the image size.
Learn to apply a median filter, a nonlinear filter in MATLAB, to remove salt and pepper noise by replacing each noisy pixel with the neighborhood median.
Design an embossing filter GUI in MATLAB using guide, with axes, panels, and labeled buttons, saving as embossing one and wiring callbacks for future functionality.
Learn to import and export pictures in MATLAB, apply an embossing filter, update the GUI image data, normalize and save the processed image with automatic extension handling.
Learn to build a MATLAB bird from ellipses using sine and cosine, then fill shapes with patch and animate via handles, integrating simple physics for movement.
Learn to add a slider to a MATLAB GUI to dynamically adjust a car image's alpha data, making it appear or disappear as you slide.
Explore histogram equalization, a simple image processing technique that reshapes pixel value distributions across the RGB channels using the HiSeq function, demonstrated with a galaxy image and a GUI.
Learn how Matlab's image processing toolbox implements histogram equalization on a galaxy image, loading and flattening color channels to vectorize data and compare original with equalized results for GUI integration.
Explore creating a MATLAB gui for image processing with four axes for the image and histograms, an import picture button, and red, green, and blue channel equalization controls.
Finalize the MATLAB GUI by wiring the import button to load and display an image with color-channel histograms. Implement selective histogram equalization for red and blue channels.
Explore how magic eye stereograms reveal depth by crossing or relaxing your eyes, and learn to create and interpret auto stereograms that visualize three-dimensional data in MATLAB.
Explore creating a magic eye image in MATLAB by converting a peaks surface into integer shift values, generating smoothed Gaussian noise, and assembling the final image through looping.
Explore how structure from motion reveals a triangle emerging from coherently moving dots in noise, using MATLAB to test point inside the triangle via the sum-of-areas method.
Learn to build a 3d rotating noisy sphere of 1000 dots with 2000 noise dots in MATLAB, using spherical coordinates and a rotation matrix to animate the dots in 3d.
Learn to build a dot kinetogram stimulus in MATLAB by generating 300 random dots with time-varying coherence using four functions: linear up, linear down, inverted-U, and U-shaped, plus random redraws.
Images are the most important ways of getting information across, ranging from art to marketing to politics. And nowadays, nearly all images are digital. Therefore, it's important to know about image processing and digital image processing.
What will you get from this course?
You will learn fundamental skills in image processing and graphical user interfaces (GUIs) in a way that is fun and engaging. Being bored while learning is a waste of everyone's time and energy, plus you really only learn when you are enjoying the learning experience. You don't need any background in image processing before taking this course.
Improving your MATLAB programming skills. This is not only about image processing related code; you'll also increase your MATLAB coding and programming skills concerning numerical processing, control statements, working with data, and more.
What are the prerequisites?
You need some basic MATLAB programming experience. If you are totally new to MATLAB, then please take an intro-MATLAB programming course first.
If you are familiar with variables, if-then statements, for-loops, and creating functions, then you have the necessary knowledge for this course.
What should you do now?
Check out the list of topics and watch the preview videos to find out if this course is right for you. If you have any questions, send me a message. You should also check out the student reviews of my other courses to see what people think about my teaching style in general.
See you in class!
Mike