noise-reduction

This question is related to my previous post Image Processing Algorithm in Matlab in stackoverflow, which I already got the results that I wanted to. But now I am facing another problem, and getting some artefacts in the process images. In my original images (stack of 600 images) I can't see any artefacts, please see the original image from finger nail: But in my 10 processed results I can see these lines: I really don't know where they come from? Also if they belong to the camera's sensor why can't I see them in my original images? Any idea? Edit: I have added the following code suggested by

hope you can help. I am recording audio from a microphone and streaming it live across a network. The quality of the samples is 11025hz, 8 bit, mono. Although there is a small delay (1 second), it works great. What I need help with is I am trying to now implement noise reduction and compression, to make the audio quieter and use less bandwidth. The audio samples are stored in a C# array of bytes[], which I am sending/receiving using Socket. Could anyone suggest how, in C#, to implement compression and noise reduction? I do not mind using a third party library as long as it is free (LGPL

I had read in a video into Visual Studio using openCV and converted it to grayscale then used the function CV_THRESH_BINARY to convert it into a binary image. However, there are holes and noise in the frames. What is a simple way to remove noise or the holes? I have read up on the Erode and Dilate functions in openCV but I am not too clear on how to use them. this is my code so far. If anyone can show me how to incorporate the noise removal into my code, it would be greatly appreciated. #include "cv.h" #include "highgui.h" int main( int argc, char* argv ) { CvCapture *capture = NULL; capture =

I have an image here with a table.. In the column on the right the background is filled with noise How to detect the areas with noise? I only want to apply some kind of filter on the parts with noise because I need to do OCR on it and any kind of filter will reduce the overall recognition And what kind of filter is the best to remove the background noise in the image? As said I need to do OCR on the image I tried some filters/operations in OpenCV and it seems to work pretty well. Step 1: Dilate the image - kernel = np.ones((5, 5), np.uint8) cv2.dilate(img, kernel, iterations = 1) As you see,

I am new to sphinx4 and speech recognition thing. I am creating a speech application by using sphinx4. The issue is noise, which results in recognition by program even without speech input by user ie it is converting speech to text even when there is no speech input by user, thus affecting accuracy. Main issue is how to implement noise reduction. This is because the system detects input even when I dont speak anything into the microphone. So I guess its because of noise. I checked online for noise reduction but there is hardly clear information about the same. Though there is some information

I want to program software for noise canceling in real time, the same way it happens in earphones with active noise canceling. Are there any open algorithms or, at least, science papers about it? A Google search found info about non-realtime noise reduction only. Ricky Bobby from This site Active noise cancelling headphones in addition to all the normal headphone circuitry, have a microphone and additional special circuitry. At a basic level the microphone on the headphone picks up the ambient noise around you and relays it to the special circuitry. The special circuitry interprets the sounds