Use amped five to copy over images and smooth out

It is used a lot in landscape and astrophotography too. The results can be utterly amazing and are one of the most powerful weapons in a forensic video analystвЂ™s arsenal.ДЇrame averaging is not just a tool for forensic image restoration and enhancement. The power of digital image processing means that we can now also stabilize objects to hold them in the same location before frame averaging. If we had a person walk through the scene, a vehicle drive by, or a bird fly through, the frame averaging would remove these and your result would be a nice, clean shot of the area where the impact of noise and the moving object is dramatically reduced. As this is color, we have values for the Red, the Green, and the Blue so that is 45,000 values for each pixel in an image! At 25 frames per second, that is 15,000 frames. You record 10 minutes of footage of a street scene on a static camera. It is now much easier to see the edges on the height chart blocks. The result being no random digital noise. In this shot of a height chart, the top image shows a single frame with the signal and compression noise.ДЄt the bottom, we have an average of 382 frames. Thanks to the wonder of powerful computers, it is possible to crunch millions and millions of values to achieve our result. Many frames go in, and a single image comes out. The resulting pixel now has a value of 179.ДЇrame averaging is a вЂmany to oneвЂ™ process. We now need to add our values together and then divide them by the number of values (6). Remember we have 256 total values between black and white (0-255) In our vehicle example, our values for the luminance at an individual pixel on each frame may be: 181, 187, 189, 175, 167, 181. frame averaging would compute the mean value of every pixel across the 6 frames so the vehicle is вЂsmoothвЂ™ once again. The vehicle would look patterned or speckled with the noise. There would be noise in each frame and that noise would be of different intensity and in different locations. Let us say you had a greyscale video of a static vehicle and you captured 6 frames. This is extremely powerful as it assists us in removing noise as well as undesired moving objects (e.g. This is a mathematical process to find the average value in a set of pixels. We will come back to this case a little later but first, let us understand the first technique, frame averaging. This is where forensic video analysis comes in, and the use of techniques to give us clean snapshots of moments in time without video noise or other moving objects and then mix those snapshots to only visualize the differences. At this point, there was no actual proof that he committed the theft. He exited seconds later with nothing in his arms.ДЄ few minutes later he was stopped in the street by local police officers and one went into the alleyway where they found the stolen container on the floor.Дuring interviews, he stated that he had nothing to do with the theft and the item was already in the alleyway when he got there. He was picked up again on street surveillance and was seen to run into an alleyway that was poorly lit. The theft itself could not be seen on the video, and the only CCTV of him running out of the store was from behind, so you could not see what was in front of him.

To help in setting the scene, let me tell you a story.ДЄ young guy decided to steal a charity box from a post office.

Use amped five to copy over images and smooth out