Is it good to use minterpolate in FFmpeg for reducing blurred frames

Question

I'm using FFMPEG to slice png files from videos.

I'm slicing the videos in fps between 1-3 depending on some video metadata. I can see that when the subjects in the video moving fast or the camera are not steady I will get blurred frames. I try to research how I can solve it (The quality of these frames is my main goal) and I tackled the minterpolate option.

I think that if I will use the blend option that will mean the 3 frames to 1 the "noise" of the blurred subjects will reduce.

So my current command now is like this:

./ffmpeg -i "/home/dev/ffmpeg/test/input/@3.mp4" -vf minterpolate=fps=1:mi_mode=blend,mpdecimate=hi=11456:lo=6720:frac=0.5 -vsync 0  "/home/dev/ffmpeg/test/output/3/(#%04d).png"

Am I right? Do you think of a better way to use FFMPEG to solve my problem?

Answer 1

You can create a better interpolation result if you use the mci method in ffmpeg, rather than the blend method. There are also more advanced techniques available.

If I understand you correctly you have a blurred image (let's call it B, in the middle) between two non-blurred images (let's call them A on the left and C on the right). Now you want to replace the middle frame B by a non-blurred version of B.

The minterpolate filter is used for interpolating in ffmpeg. It has two different approaches. A blend mode, which fades out A and then fades in C to generate a new image for B.

Blend

If I run it with ffmpeg -i %02d.png -framerate 10 -vf minterpolate=fps=20:mi_mode=blend test-%02d.png I get the following image.

Motion estimation

You can also use the motion estimation or mci mode, which allows you to do motion based interpolation. You can call it by changing the mode: ffmpeg -i %02d.png -framerate 10 -vf minterpolate=fps=20:mi_mode=mci test-%02d.png That generates a circle in the middle.

Going further

The ffmpeg mci mode uses a classic algorithm. There are some more advanced optical flow and neural network based approaches available. Which can give better results with more complex images and with more complex motion fields.