Calculating FIR filter coefficients with the windowing method using the Rectangular Window

Please advice how to calculate FIR filter coefficients with windowing method using the Rectangular Window function and convolution method (using the Output Side Algorithm from Chapter 6)

Answer 1

[Image Analyst]

Just create a 2D array of weights using whatever way you want. For example to get a Gaussian use fspecial():

kernel = fspecial('Gaussian', 15, 5)
outputImage = conv2(double(inputImage), kernel, 'same'); % Blur the image

[Sundeks]

Its audio signal, not the images. What application can calculate this?

[Image Analyst]

conv() is for 1-D signals

window = ones(1, 9); % Whatever length you want
output = conv(signal, window, 'same');

Change the numbers in the window kernel to do various kinds of filters. If they're uniform, it's known as a moving average or box filter.