Locally adaptive multiscale contrast optimization

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.