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In this paper, we present a new method for brightness elimination in chromatic images by means of the extension of the morphological reconstruction for colour images. We use the HSI colour space for morphological processing, after solving certain inconveniences present in this colour model. We investigate the connected filters of the mathematical morphology and, in particular, the so-called filters by reconstruction. These filters are formally defined for colour images. The power of the morphological reconstruction for brightness elimination in colour images is presented. We also describe a new algorithm to control the oversimplification of images and to reduce the high processing cost of the geodesic operations. Examples of its application are shown. The new method proposed here achieves good results, which are similar to those obtained from other techniques, yet does not require either costly multiple-view systems or stereo images.

In this paper, we present a new method for brightness elimination in chromatic images by means of the extension of the morphological reconstruction for colour images. We use the HSI colour space for morphological processing, after solving certain inconveniences present in this colour model. We investigate the connected filters of the mathematical morphology and, in particular, the so-called filters by reconstruction. These filters are formally defined for colour images. The power of the morphological reconstruction for brightness elimination in colour images is presented. We also describe a new algorithm to control the oversimplification of images and to reduce the high processing cost of the geodesic operations. Examples of its application are shown. The new method proposed here achieves good results, which are similar to those obtained from other techniques, yet does not require either costly multiple-view systems or stereo images.

This paper presents an algorithm for automatic neural image analysis in immunostained vertebrate retinas. We present a useful tool for cell quantification avoiding the lost of information of traditional binary techniques in automatic recognition of images. The application is based on the extension of the mathematical morphology to colour images. In the paper, we define the basics and more complex morphological operations to vectorial image processing. We propose and demonstrate a colour image reconstruction by geodesic transformations. In addition, we adapt the morphological segmentation of greyscale image to the segmentation of multispectral images of retinas of monkeys.

This paper presents an algorithm for automatic neural image analysis in immunostained vertebrate retinas. We present a useful tool for cell quantification avoiding the lost of information of traditional binary techniques in automatic recognition of images. The application is based on the extension of the mathematical morphology to colour images. In the paper, we define the basics and more complex morphological operations to vectorial image processing. We propose and demonstrate a colour image reconstruction by geodesic transformations. In addition, we adapt the morphological segmentation of greyscale image to the segmentation of multispectral images of retinas of monkeys.