title: Detecting noise frames
body: <p>I have a FPV (First Person View) receiver that shows receiving frames from a FPV camera mounted on a drone. When the transmitter is working, receiver shows a camera view. Otherwise, if connection is lost or the transmitter is not working, it shows noise frames. </p>
  
  <p>The noise frames have random patterns (sometimes with more white pixels and sometimes with more black pixels). I want to detect those noise frames using OpenCV in Python in an efficient way. I know that OpenCV has a method called <code>cv2.fastNlMeansDenoisingColored()</code>. But in this case, I want to detect the noise frames not noise in each frame. </p>
  
  <p>A sample of noise frames is attached:</p>
  
  <p><a href="https://i.stack.imgur.com/Xz9l0.png" rel="noreferrer"><img src="https://i.stack.imgur.com/Xz9l0.png" alt="enter image description here"></a></p>
  
  <p>Another noise frame example: </p>
  
  <p><a href="https://i.stack.imgur.com/9ZPAj.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/9ZPAj.jpg" alt="enter image description here"></a></p>
  
  <p>A valid frame (that could be anything):</p>
  
  <p><a href="https://i.stack.imgur.com/0FNPQ.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/0FNPQ.jpg" alt="enter image description here"></a></p>