Calculating sharpness of an image

问题

I found on the internet that laplacian method is quite good technique to compute the sharpness of a image. I was trying to implement it in opencv 2.4.10. How can I get the sharpness measure after applying the Laplacian function? Below is the code:

Mat src_gray, dst;
int kernel_size = 3;
int scale = 1;
int delta = 0;
int ddepth = CV_16S;

GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );

/// Convert the image to grayscale
cvtColor( src, src_gray, CV_RGB2GRAY );

/// Apply Laplace function
Mat abs_dst;

Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, BORDER_DEFAULT );

//compute sharpness
??

Can someone please guide me on this?

回答1:

Possible duplicate of: Is there a way to detect if an image is blurry?

so your focus measure is:

cv::Laplacian(src_gray, dst, CV_64F);

cv::Scalar mu, sigma;
cv::meanStdDev(dst, mu, sigma);

double focusMeasure = sigma.val[0] * sigma.val[0];

---

Edit #1:

Okay, so a well focused image is expected to have sharper edges, so the use of image gradients are instrumental in order to determine a reliable focus measure. Given an image gradient, the focus measure have to pool the data at each point as an unique value.

The use of second derivatives is one technique for passing the high spatial frequencies, which are associated with sharp edges. As a second derivative operator we use the Laplacian operator, that can be approximate using the mask:

Foor pooling the data at each point, we use two methods. The first one is the sum of all the absolute values, driving to the following focus measure:

where L(m, n) is the convolution of the input image I(m, n) with the mask L. The second method calculates the variance of the absolute values, providing a new focus measure given by:

where L overline is the mean of absolute values.

Read the article

J.L. Pech-Pacheco, G. Cristobal, J. Chamorro-Martinez, J. Fernandez-Valdivia, "Diatom autofocusing in brightfield microscopy: a comparative study", 15th International Conference on Pattern Recognition, 2000. (Volume:3 )

for more information.

回答2:

This article helped me in blurring, sharpening, embossing, edge detection in my frame. Kernal Image Processing

I used the above help in android application. I will publish the link and source code of an app once I complete.

Hope this helps. Happy coding :)

来源：https://stackoverflow.com/questions/28717054/calculating-sharpness-of-an-image