title: Feature Detection in Noisy Images
body: <p>I've built an imaging system with a webcam and feature matching such that as I move the camera around; I can track the camera's motion. I am doing something similar to <a href="http://opencv.itseez.com/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.html#feature-flann-matcher" rel="nofollow noreferrer">here</a>, except with the webcam frames as the input.</p>
  
  <p>It works really well for "good" images, but when taking images in really low light lots of noise appears (camera high gain), and that messes with the feature detection and matching. Basically, it doesn't detect any good features, and when it does, it cannot match them correctly between frames.</p>
  
  <p>Does anyone know a good solution for this? What other methods are used for finding and matching features?</p>
  
  <p>Here are two example images with very low features:</p>
  
  <p><img src="https://i.stack.imgur.com/oYhGS.jpg" alt="Frame 1"></p>
  
  <p><img src="https://i.stack.imgur.com/yS9rr.jpg" alt="Frame 2"></p>