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Shape-from-focus (SFF) has widely been studied in computer vision as a passive depth recovery and 3D reconstruction method. One of the main stages in SFF is the computation of the focus level for every pixel of an image by means of a focus measure operator. In this work, a methodology to compare the performance of different focus measure operators for(More)
The limited depth-of-field of some cameras prevents them from capturing perfectly focused images when the imaged scene covers a large distance range. In order to compensate for this problem, image fusion has been exploited for combining images captured with different camera settings, thus yielding a higher quality all-in-focus image. Since most current(More)
This paper presents a new technique for combining multiple texture feature extraction method s in ord er to classify the pixels of an input image into a set of texture mod els of interest. The problem of integrating multiple texture method s for classification purposes is cast as a collaborativ e d ecision mak ing problem. E ach texture method is consid(More)
This paper presents a new, efficient technique for supervised texture segmentation based on a set of specifically designed filters and a multi-level pixel-based classifier. Filter design is carried out by means of a neural network, which is trained to maximize the filters' discrimination power among the texture classes under consideration. Texture features(More)