I. INTRODUCTION
T
HERE are some fairly powerful techniques for image de-
blurring [1], [2], [3]. The typical problem of image de-
blurring methods is finding optimal parameters for a compro-
mise between smooth result with blurry edges and sharp result
with artifacts like ringing or noise amplification. In this work
we present a new post-processing algorithm for image deblur-
ring with enhancement of edge sharpness.
We localize the area of interest to the neighborhood of the
edges. The idea is to transform the neighborhood of the blurred
edge so that the neighboring pixels move closer to the edge, and
then resample the image from the warped grid to the original
uniform grid.
The warping approach is related to the morphology-based
sharpening [4] and shock filters [5], [6], [7]. But these methods
make the image appear piecewise constant which is effective
mostly for cartoon-like images. The proposed method is ap-
plied to edges locally so the textures are preserved a priori, also
warping compresses the edge neighborhood at fixed rate and
does not make the image piecewise constant.
The warping approach for image enhancement was intro-
duced in [8]. The warping of the grid is performed according
to the solution of a differential equation that is derived from
the warping process constraints. The solution of the equation