Logic behind unsharp filter in matlab I am trying to understand the logic behind unsharp filter in matlab. If I type:

image = imread('nameoffile');
filter = fspecial('unsharp', 0.5);
resultImage = imfilter(image, filter);


resultImage is sharper than image. I opened fspecial.m file and saw that unsharp filter is created as:

 h = [0 0 0;0 1 0;0 0 0] - fspecial('laplacian',alpha);


If I filter an image with this matrix:

[0 0 0;
 0 1 0;
 0 0 0;]


result image is the same with original one. I know laplacian filter detects sharp edges. So, if we subtract sharp edges from an image we must get blurred image, I suppose. However, if we filter an image with h matrix(unsharp filter), we get sharper image. I did not understand the logic.
The Laplacian filter does actually outputs values of 0 on edges, and positive/negative inside image regions. Edges are detected as zero-crossings of the Laplacian. 
This makes sense if you remember that the Laplacian is a second-order derivative, and not a first order.

So, the unsharp filter that you describe computes (identity - Laplacian) convoluted with the image, i.e., the image minus something that is zero on edges. Hence, high frequencies (edges) are not attenuated while lower frequencies are weakened.