Computer Vision: Convolution Basics

These are some of the questions every data scientist encounter at least once in their deep learning journey. I have these questions now and then. So, mathematically speaking, convolution is an operator on two functions (matrices) that produces a third function (matrix), which is the modified input by the other having different features (values in the matrix). In Computer Vision, convolution is generally used to extract or create a feature map (with the help of kernels) out of the input image. In the above image, the blue matrix is the input and the green matrix is the output.