In this project, I worked with a team of students to explore various techniques for manipulating digital images, treating them as matrices of pixels. The project focused on applying matrix operations to image data, beginning with transformation matrices and progressing to image compression. By using MATLAB, we were able to transform images through operations such as rotation, scaling, and translation, and then compress images to reduce file sizes while maintaining quality.
Python Application: The concepts applied in MATLAB are highly transferable to Python. With Python’s powerful libraries such as NumPy (for matrix operations), Matplotlib and Seaborn (for data visualization), and SciPy (for algorithmic development), the same data processing, visualization, and computational techniques can be implemented. Python’s versatility and ease of use make it an excellent alternative for replicating the work done in MATLAB, ensuring that similar results can be achieved with both platforms.
