USAGE: sharp [-m method] [-s sharpen] infile outfile
USAGE: sharp [-st] infile
USAGE: sharp [-h or -help]

-m ............ method ....... method=0 is edge extract; method=1 is sharpen
.............................. default=1
-f ............ factor ....... sharpening/edge extraction gain factor;
.............................. factor>=0; float; default=2
-st .......................... get image statistics
-h or -help .................. get help

PURPOSE: To sharpen an image or extract edges adaptively.

DESCRIPTION: SHARP is an adaptive technique to either sharpen an image or extract edges. It applies an adaptive gain factor based upon the image's local standard deviation to a high pass filtered version of the image and adds that to a low pass filtered version of the image.

The adaptive formula R = method*M + G*H. Here R is the resulting image. M is the low pass filtered image which is the local mean image generated by applying a 3x3 average convolution to the input image, I. H = (I - M) is the high pass filtered image. G is the gain image, which is computed as G = (factor*std)/(S + (factor*std/mg)). Here std is the image's global standard deviation, mg is a maximum gain constant and S is the image's local standard deviation in the 3x3 neighborhood.

ARGUMENTS:

-m method - method is either 0 or 1. A value of 0 for method indicates edge extraction and value of 1 for method indicates sharpening. The default=1.

-f factor factor is the sharpening/edge extraction gain factor. It is a multiplier to the image's actual standard deviation. The value for factor must be greater than or equal to 0. A value of about 0.5 leaves the image nearly unchanged. A smaller value blurs the image or extract more edges. A larger value sharpens the image or extracts fewer edges. This transition value is not exact and is likely image statistics dependent as the result is a mix of the low pass filtered image (not the original image) and the adaptive high pass filtered image. Factor is floating point number. The default=2.

CAVEAT: No guarantee that this script will work on all platforms, nor that trapping of inconsistent parameters is complete and foolproof. Use At Your Own Risk.