2D convolution with the signal processing module in SciPy
Now, let's take a look at the mathematical background of convolution. Convolution is understanding how the shape of a function is affected by another function. The process of computing it and the resultant function is known as a convolution. We can perform convolutions on 1D, 2D, and multidimensional data. Signals are multidimensional entities. Images are a type of signal. So, we can apply convolution to an image.
Note
You can read more about convolution at http://www.songho.ca/dsp/convolution/convolution2d_example.html.
We can perform convolution operations on images with various kernels to process images. For that, we will learn how to use the signal module from SciPy. Let's install the SciPy library with the following command:
pip3 install scipy
We can perform convolution operations on images with various kernels to process images. The function that performs convolution on 2D data is signal.convolve2d...