signal processing vs image processing?
"General" DSP (and signal processing in general) tends to deal much more with problems that can be solved with linear filters, or at least a preponderance of linear filtering, and there's a lot more content involving 1-D signals -- so you tend to see a lot of emphasis on frequency-domain analysis and FFT (and even some folks who can't seem to distinguish between typing 'fft' in Matlab and understanding DSP).

Image processing (video processing in particular) tends to deal with problems that must be solved with lots of nonlinear processing -- image segmentation, finding edges, etc.  Even super-duper neural networks have significant nonlinearities.  While there are linear operations (i.e., convolution, cross-correlation) these tend to be processor-intensive, and are used sparingly.

One can go through an entire career in DSP and not do image processing, and visa-versa (I'm a case in point, with around 30 years experience in DSP and digital control systems, yet with very little image processing under my belt).

About the only thing that is really common, besides the fact that you're taking in something you could call a "signal" and you're doing something to it you could call "processing", is that "plain old" DSP and image processing both reward the practitioner who's willing to do the hard math (or who's lucky enough to find the hard math easy).  

It also helps to be able to make intuitive leaps to potential solutions, and then do the hard math to back-fill to determine that your solution will actually work, to refine it, and to be on a firm mathematical foundation for your next intuitive leap.