Improved Digital Image Restoration Algorithm Based on Criminisi
DAI Lei, JIANG Dai-Hong, DING Bin, James K Hahn 
Journal of Digital Information Management, Vol. 14, No. 5, 2016.
DOI: 
Link: http://dline.info/fpaper/jdim/v14i5/jdimv14i5_3.pdf
Abstract:
Digital image inpainting pertains to the
reconstruction of missing or damaged portions of images
in a manner that is not detectable to the observer. This
study evaluates the Criminisi algorithm for digital image
inpainting and proposes four improvements. First, a new
priority function was introduced using piecewise function
to adjust the sequence of inpainting process and change
the operation used from multiplication to addition under
certain conditions. This adjustment improved the flexibility
of the algorithm thereby avoiding incorrect filling sequence
caused by rapid decay of data term. Second, Sobel
operator instead of the traditional gradient direction was
used to improve the computation of isophote. This
approach first restored points on the isophote, which is
beneficial to information fusion. Third, a new matching
function was proposed and a new matching search method
was employed to identify samples in the neighborhood of
the damaged region based on similarity. This improvement
created the nearest optimal matching block used for
inpainting. Finally, a new formula of smoothing error
propagation for updating confidence value was defined.
This method ensured the correct sequence of synthesis
from the periphery to the center. Experimental results show
that this improved algorithm yields satisfactory inpainting
results and improves repair efficiency.