Multiscale image enhancement and segmentation based on morphological connected contrast mappings. (English) Zbl 1198.68268

Terol-Villalobos, Iván R.

Monroy, Raúl (ed.) et al., MICAI 2004: Advances in artificial intelligence. Third Mexican international conference on artificial intelligence, Mexico City, Mexico, April 26–30, 2004. Proceedings. Berlin: Springer (ISBN 3-540-21459-3/pbk). Lecture Notes in Computer Science 2972. Lecture Notes in Artificial Intelligence, 662-671 (2004).

Summary: This work presents a multiscale image approach for contrast enhancement and segmentation based on a composition of contrast operators. The contrast operators are built by means of the opening and closing by reconstruction. The operator that works on bright regions uses the opening and the identity as primitives, while the one working on the dark zones uses the closing and the identity as primitives. To select the primitives, a contrast criterion given by the connected tophat transformation is proposed. This choice enables us to introduce a well-defined contrast in the output image. By applying these operators by composition according to the scale parameter, the output image not only preserves a well-defined contrast at each scale, but also increases the contrast at finer scales. Because of the use of connected transformations to build these operators, the principal edges of the input image are preserved and enhanced in the output image. Finally, these operators are improved by applying an anamorphosis to the regions verifying the criterion.
For the entire collection see [Zbl 1046.68012].

MSC:

68T45	Machine vision and scene understanding
68U10	Computing methodologies for image processing