Previously the pyramid was done with a rescaling factor of 2 (implied by the
use of pyrDown). This often leads to inferior results compared to a scale step
of e.g. 0.8 (a factor of 2 is obviously faster). This commit makes the scale
step configurable and uses a resonable default value.

The other change in this commit is that median filtering is added. This is not
described in this paper but it is done in the author's implementation. (See
e.g. "Secrets of optical flow estimation and their principles", Sun et al.,
CVPR 2010) This serves as periodic outlier removal during optimization, leading
to smoother flow fields while preserving motion edges. This includes splitting
the optimization loop into two loops.

houghlines.py for HoughLinesP() and HoughLines()
houghcircles.py for HoughCircles()

sample code : https://github.com/Itseez/opencv/blob/master/samples/cpp/tutorial_code/features2D/SURF_descriptor.cpp

Bug #2888

http://code.opencv.org/issues/2926