motion-blur

I want to detect how blurred an image is, may be It can be called "blur extend". I found a useful paper for this: http://www.cs.cmu.edu/~htong/pdf/ICME04_tong.pdf I used OpenCV and implemented all steps from this paper, but the result is not same as result from this paper. Can someone give me any advise for detecting "blur extend"? ErmIg You can detect a blurring image with using next algorithm: Convert the image into gray format. Calculate the maximal absolute second derivative from the gray image (for every point): d[x,y] = max(abs(2*d[x,y] - d[x,y+1] -d[x,y-1]), abs(2*d[x,y] - d[x+1,y] -d[x

This question already has an answer here: HTML5 Canvas Motion Blur effect? 2 answers I'm wondering how to make a motion blur in javascript/jquery. I've an horizontal gallery and I want to apply the motion blur when the images are moving. Actually, It works perfectly with that way : an overlay image with a motion blur (photoshop) and the opacity varies depending to the speed of the images. The render looks pretty good but i need to load 2 times all my images and it sucks. In html : <div id="slider wrapper"> <ul> <li> <a href=""> <img src="img1.jpg"/> <img src="img1_blur.jpg"/> </a> </li> <li>

I am trying to implement the Wiener Filter to perform deconvolution on blurred image. My implementation is like this import numpy as np from numpy.fft import fft2, ifft2 def wiener_filter(img, kernel, K = 10): dummy = np.copy(img) kernel = np.pad(kernel, [(0, dummy.shape[0] - kernel.shape[0]), (0, dummy.shape[1] - kernel.shape[1])], 'constant') # Fourier Transform dummy = fft2(dummy) kernel = fft2(kernel) kernel = np.conj(kernel) / (np.abs(kernel) ** 2 + K) dummy = dummy * kernel dummy = np.abs(ifft2(dummy)) return np.uint8(dummy) This implementation is based on the Wiki Page . The TIFF image