Detail Enhancement for Infrared Images Based on Propagated Image Filter

For displaying high-dynamic-range images acquired by thermal camera systems, 14-bit raw infrared data should map into 8-bit gray values. This paper presents a new method for detail enhancement of infrared images to display the image with a relatively satisfied contrast and brightness, rich detail information, and no artifacts caused by the image processing. We first adopt a propagated image filter to smooth the input image and separate the image into the base layer and the detail layer. Then, we refine the base layer by using modified histogram projection for compressing. Meanwhile, the adaptive weights derived from the layer decomposition processing are used as the strict gain control for the detail layer. The final display result is obtained by recombining the two modified layers. Experimental results on both cooled and uncooled infrared data verify that the proposed method outperforms the method based on log-power histogram modification and bilateral filter-based detail enhancement in both detail enhancement and visual effect

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Novel melanoma diagnosis and prognosis methods based on 3D fringe projection

This project aims to find an effective and non-invasive methodology to assist in the diagnosis of skin lesions using 3D profile features.Este proyecto tiene como objetivo el desarrollo de una metodología eficaz y no invasiva para la asistencia en el diagnóstico de lesiones cutáneas utilizando sus características 3D.Aquest projecte té com a objectiu desenvolupar una metodologia no invasiva i eficaç per ajudar en el diagnòstic de lesions de la pell mitjançant caraterístiques 3D

A new color constancy algorithm based on the histogram of feasible mappings

International Conference on Image Analysis and Recognition (ICIAR), 2005, Toronto (Canada)Color is an important cue both in machine vision and image processing applications, despite its dependence upon illumination changes. We propose a color constancy algorithm that estimates both the set and the likelihood of feasible color mappings in respect to their frequency and effectiveness. The best among this set is selected to rendered back image colors as seen under a canonical light. Experiments were done to evaluate its performance compared to Finlayson’s 2D gamut–mapping algorithm, outperforming it. Our approach is a helpful alternative wherever illumination is poorly known since it employs only image data.This work was supported by the project 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).Peer Reviewe