Locally adaptive multiscale contrast optimization
Appears in:
Proc. 12th IEEE Int'l Conf on Image Processing
vol I, pages 949-952. Genoa, Italy, September 2005.
© IEEE Computer Society.
We describe a method for automatically and adaptively boosting the
visibility of local features in an image. A log intensity image is
first decomposed into a set of subbands at multiple scales and
orientations. Operating successively from coarse frequency bands to
fine, the coefficients of each subband are adjusted so as to move
their locally averaged amplitudes toward a target value using a gamma
operation. Target values are chosen to fall linearly over scale,
consistent with a scale-invariant spectral model. To avoid enlarging
the range of image intensity values, in those locations where the
local mean is near the minimal or maximal values of the image and the
local contrast is being boosted significantly, the local mean is moved
toward the global mean. Finally, a spatial mask is applied in the
pixel domain to ensure that the enhancements are applied only in the
vicinity of image features. The resulting image appears to be both
sharper and of higher contrast.
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