'**SUMMARY**
This method applies unsharp mask or highboost filtering
on image depending upon the boost value provided.
DFT is applied on image using gaussian lowpass filter.
A mask is created subtracting the DFT image from the original
iamge. And then mask is added in the image to sharpen it.
unsharp masking => image + mask
highboost filtering => image + (boost)*mask
**PARAMETERS**
* *boost* - int  boost = 1 => unsharp masking, boost > 1 => highboost filtering
* *dia* - int Diameter of Gaussian low pass filter
* *grayscale* - BOOL
**EXAMPLE**
Gaussian Filters:
>>> im = Image("lenna")
>>> img = im.applyUnsharpMask(2,grayscale=False) #highboost filtering
output image: http://i.imgur.com/A1pZf.png
>>> img = im.applyUnsharpMask(1,grayscale=False) #unsharp masking
output image: http://i.imgur.com/smCdL.png
>>> im = Image("grayscale_lenn.png") #take image from here: http://i.imgur.com/O0gZn.png
>>> img = im.applyUnsharpMask(2,grayscale=True) #highboost filtering
output image: http://i.imgur.com/VtGzl.png
>>> img = im.applyUnsharpMask(1,grayscale=True) #unsharp masking
output image: http://i.imgur.com/bywny.png
**SEE ALSO**
:py:meth:`rawDFTImage`
:py:meth:`getDFTLogMagnitude`
:py:meth:`applyDFTFilter`
:py:meth:`highPassFilter`
:py:meth:`lowPassFilter`
:py:meth:`bandPassFilter`
:py:meth:`InverseDFT`
:py:meth:`applyButterworthFilter`
:py:meth:`InverseDFT`
:py:meth:`applyGaussianFilter`
:py:meth:`applyUnsharpMask`'

def applyUnsharpMask(self, boost=1, dia=400, grayscale=False):

    if (boost < 0):
        print 'boost    >=    1'
        return None
    lpIm = self.applyGaussianFilter(dia=dia, grayscale=grayscale, highpass=False)
    im = Image(self.getBitmap())
    mask = (im - lpIm)
    img = im
    for i in range(boost):
        img = (img + mask)
    return img
