algorithm based on Mask technique. The background image
is obtained based on the definitions of different image
regions. In this way, it can reflect the lightness trend of the
image more accurately. In addition, stretching the image after
subtraction with different linear transformation models
improves the uneven contrast phenomenon in the original
image.
Through the experiment, the correctness and validity of this
algorithm are proved, but this algorithm still needs to be
improved in the following aspects:
(1)How to set the size of the image blocks more
appropriately is a difficulty. If the size is too big, the filtering
method based on the definition can't achieve the expected
effect. If the size is too small, this will make the lightness of
the different image regions be approximately the same,
which means dodging is excessive.
(2)How should we set the values of some parameters, such as
the maximum and minimum cut-off frequency automatically?
The selection of these parameters will directly influence the
final dodging effect.
(3)In order to remove more detailed information from the
background image, we can obtain the background image
using the filters with different cut-off frequencies based on
classification of ground objects. This is a recommended topic
for a proposed follow-on study.
REFERENCES
Blohm W.,1997. Lightness Determination at Curved
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