Fundamentals of digital image processing
Fundamentals of digital image processing
Contrast enhancement technique based on local detection of edges
Computer Vision, Graphics, and Image Processing
Morphological signal processing and the slope transform
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
Toggle mappings and some related transformations: a study of contrast enhancement
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Granulometries and opening trees
Fundamenta Informaticae - Special issue on mathematical morphology
Connections for sets and functions
Fundamenta Informaticae - Special issue on mathematical morphology
Granulometric Size Density for Segmented Random-Disk Models
Journal of Mathematical Imaging and Vision
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Transform-based image enhancement algorithms with performance measure
IEEE Transactions on Image Processing
A nonlinear image contrast sharpening approach based on Munsell's scale
IEEE Transactions on Image Processing
Morphological grayscale reconstruction in image analysis: applications and efficient algorithms
IEEE Transactions on Image Processing
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
Morphological Connected Filtering on Viscous Lattices
Journal of Mathematical Imaging and Vision
Morphological contrast index based on the Weber's law
International Journal of Imaging Systems and Technology
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In this paper a morphological contrast measure is introduced. The quantification of the contrast is based on the analysis of the edges, which are associated with substantial changes in luminance. Due to this, the contrast measure is used to detect the image that presents a high visual contrast when a set of output images is analyzed. The set of output images is obtained by application of morphological contrast mappings with size criteria. These contrast transformations are defined under the notion of partitions generated by the set of flat zones of the image; therefore, they are connected transformations. In addition, an application to the segmentation of white and grey matter in brain magnetic resonance images (MRI) is provided. The detection of white matter is carried out by means of a contrast mapping with specific control parameters; subsequently, white and grey matter are separated and their ratio is calculated and compared with manual segmentations. Also, an example of segmentation of white and grey matter in MRI corrupted by 5% noise is presented in order to observe the performance of the morphological transformations proposed in this work.