Explore image transformation techniques in this MIT Computational Thinking lecture from the Spring 2021 series. Dive into topics such as downsampling, upsampling, linear combinations, element-wise multiplication, convex combinations, and image filtering using convolutions. Learn about the Unitful.jl package for adding units to numbers in Julia, and gain insights into computer science concepts like complexity, GPU architectures, and data structures. Discover practical applications through Photoshop-like manipulations and examine various kernels, including the Gaussian filter. Conclude with a discussion on discrete vs. continuous representations and boundary handling in image processing.