No.

Oh, I need to read your post. The title is a little incomplete.

If you're linearly interpolating, there is that $\operatorname{sinc}^2 \left( \frac{f}{f_\mathrm{s}} \right)$ filtering, this puts zeros exactly on all non-zero integer multiples of your sample rate (where the images go). That kills a lot of your images, at least at low frequencies (that are close to $k \cdot f_\mathrm{s}$). Perhaps you might want to LPF to remove high frequency components that will image at frequencies distance away from these zeros.

But you'll lose content. You might want to consider doing a simple polyphase resampling, but if you wanna do it with linear interpolation, that works well in many cases.

Can interpolation introduce aliasing?

Crappy interpolation can. Aliasing can happen during resampling if those images aren't well attenuated.

If you're linearly interpolating, there is that $\operatorname{sinc}^2 \left( \frac{f}{f_\mathrm{s}} \right)$ filtering, this puts zeros exactly on all non-zero integer multiples of your sample rate (where the images go). That kills a lot of your images, at least at low frequencies (that are close to $k \cdot f_\mathrm{s}$). Perhaps you might want to LPF to remove high frequency components that will image at frequencies distance away from these zeros.

But you'll lose content. You might want to consider doing a simple polyphase resampling, but if you wanna do it with linear interpolation, that works well in many cases.

Can interpolation introduce aliasing?

Crappy interpolation can. Aliasing can happen during resampling if those images aren't well attenuated.

This is a paper that Duane Wise and I wrote about polynomial interpolation about a quarter century ago. Linear interpolation is 1st-order polynomial interpolation. The more that you're oversampled (that is the lower the ratio of content bandwidth to Nyquist frequency), the better that linear interpolation will sound.

But you might very well want to low-pass filter a little before the linear interpolation. And in doing so, you can compensate for some of the rolloff that naturally comes from linear interpolation. I'll try to post up a figure showing this later.

No.

But since Body must be at least 30 characters; you entered 3.

No.

Oh, I need to read your post. The title is a little incomplete.

If you're linearly interpolating, there is that $\operatorname{sinc}^2 \left( \frac{f}{f_\mathrm{s}} \right)$ filtering, this puts zeros exactly on all non-zero integer multiples of your sample rate (where the images go). That kills a lot of your images, at least at low frequencies (that are close to $k \cdot f_\mathrm{s}$). Perhaps you might want to LPF to remove high frequency components that will image at frequencies distance away from these zeros.

But you'll lose content. You might want to consider doing a simple polyphase resampling, but if you wanna do it with linear interpolation, that works well in many cases.

Can interpolation introduce aliasing?

Crappy interpolation can. Aliasing can happen during resampling if those images aren't well attenuated.