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Does anyone know of any resources that explain simply, these are the data objects and variable definitions involved when doing sound processing?

I took a class on image processing where we learned about various kernels and how to apply those to images, this process is very simple and clear as can be seen by the pencil and paper used in this video https://www.youtube.com/watch?v=ySAEWNk5Il4

Image processing is very straightforward to me. Two 2-d arrays of pixels, one kernel, this is how to apply the kernel to one 2-d array to get the resulting 2-d array. A kernel that looks like this will function like this. . .

Sound processing is either much more complicated or the people that understand it don't like pencils and paper.

Does anyone know of any resources that explain simply, these are the data objects and variable definitions involved when doing sound processing?

So far I've found a lot of python libraries and snippets of code with very convoluted variable names. Looking for something more psuedo-code and basic, preferably some pencil and paper examples.

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    $\begingroup$ Hi there! I have good news for you; If image processing is so simple to you, then audio processing is even simpler! Just think of one single row or column of a 2D image: that's your audio data now. And just think of one row or column of your 2D filter kernel, and that's your 1D filter... and that's it... ;-) $\endgroup$ – Fat32 Jan 21 '19 at 17:24
  • $\begingroup$ In my case, image processing (2D) was taught as a generalisation of signal processing (1D). My perception is that the way this question is phrased makes it too broad. Also, there are some good responses to questions about books on DSP on this board and as far as I am aware, the majority of these books do adopt a pen-and-pencil approach rather than talk about "code". $\endgroup$ – A_A Jan 21 '19 at 17:43
  • $\begingroup$ Hmm, maybe I came off too confident in my question :) I'm getting lost with what is in my 1D array? They aren't RGB values. Are they amplitude? What do I do with the imaginary numbers from a resulting FFT? What does an example Kernel look like, and how is it applied? I don't really mean to ask those questions specifically, but hoping someone could point me to a good resource. I will check out the books, I've mostly just been searching the internet, maybe I will have some better luck with a book. Thank you guys! $\endgroup$ – Garrett Hartley Jan 23 '19 at 0:23