Predicting earthquakes using disturbances in DTH TV transmission It is said that before an earthquake happens, a viewer experiences disturbances in DTH TV transmission in the form of distorted images on the screen which automatically correct after a few seconds.

Is it possible to identify patterns of such disturbances by continuously monitoring TV images so that earthquakes can potentially be predicted at least few minutes in advance and many lives could be saved?
I think that if there are disturbances caused by something preceding earthquake, they might be used.

The problem is that you need to find which cause produces that effect and measure it. For example you can team up with geologists, geophysicists or someone similar and try to build as complete hypothesis as possible and then design experiment to gather data. If your experiment would bring some non noise data then you can start to thinking about machine learning algorithms which will work in this situation.

But you might also try to do it on "brute force" way by actually recording DTH TV images in seismically unstable regions and try to correlate those videos with seismic data. Then after some manual examination and categorization you could define (or not if this cause and effect hypothesis is wrong) some possible glitches that are observed and try to develop software that tries to detect them (OpenCV might be useful for example).

IMHO in either way, some domain knowledge related to earthquakes would be more useful on beginning stage, and experience related to machine learning would be more useful on latest stages of such ambitious project.