def __init__(self,imfilename,flatfilename='',flatdata=[]):
self._Image,self._imageData=self.parseImage2(imfilename)
if flatfilename!='':
self._flatImage,flatdata=self.parseImage2(flatfilename)
del(self._flatImage)
if len(flatdata)==len(self._imageData):
self._imageData=arrlog(array(flatdata)/self._imageData)
self._imageMask=arrabs(array(self._imageData))>-1
self._opts={}
self._opts['readMode']=1 # 0 is raw, 1 mask-values, 2 masked image
self._opts['usingMat']=0
self._opts['maskMode']=0 # 0 default, -1 values under thresh, 1 values overthresh
self._impResults={}
def matchImage(self,otherImage,toFlip=True):
# Does a correlation between two images
if toFlip:
tData=fliplr(otherImage._imageData)
else:
tData=otherImage._imageData
tempData=ifftshift(abs(ifft2(fft2(self._imageData)*fft2(tData).conj())))
del(tData)
wArg=tempData.argmax()
xOff=(wArg % tempData.shape[1])
yOff=round((wArg-xOff)/tempData.shape[1])
# find vector from center
xOff-=tempData.shape[1]/2.0
yOff-=tempData.shape[0]/2.0
self.matchedPos=(xOff,yOff)
self._impResults['Maximum Correlation']=(xOff,yOff)
return arrlog(tempData) # easier to visualize