Search results for "Pixel"
showing 10 items of 421 documents
Automatic Detection of Hemangioma through a Cascade of Self-organizing Map Clustering and Morphological Operators
2016
Abstract In this paper we propose a method for the automatic detection of hemangioma regions, consisting of a cascade of algorithms: a Self Organizing Map (SOM) for clustering the image pixels in 25 classes (using a 5x5 output layer) followed by a morphological method of reducing the number of classes (MMRNC) to only two classes: hemangioma and non-hemangioma. We named this method SOM-MMRNC. To evaluate the performance of the proposed method we have used Fuzzy C-means (FCM) for comparison. The algorithms were tested on 33 images; for most images, the proposed method and FCM obtain similar overall scores, within one percent of each other. However, in about 18% of the cases, there is a signif…
Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering
2011
In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. Three features are extracted from the tested image. The features are scaled down by a factor of 2 and mapped into a Self-Organizing Map. A modified Fuzzy C-Means clustering algorithm is used to divide the neuron units of the map in 2 classes. The entire image is again input for the Self-Organizing Map and the class of each pixel will be the class of its best matching unit in the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the DRIVE database shows accurate ex…
Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and K-Means Clustering
2011
In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. A Self-Organizing Map is trained on a portion of the same image that is tested and K-means clustering algorithm is used to divide the map units in 2 classes. The entire image is again input for the Self-Organizing Map, and the class of each pixel will be the class of the best matching unit on the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the publicly available DRIVE database shows accurate extraction of vessels network and a good agreement between our segm…
Computation and Display of 3D Movie From a Single Integral Photography
2016
Integral photography is an auto-stereoscopic technique that allows, among other interesting applications, the display of 3D images with full parallax and avoids the painful effects of the accommodation-convergence conflict. Currently, one of the main drawbacks of this technology is the need of a huge amount of data, which have to be stored and transmitted. This is due to the fact that behind every visual resolution unit, i.e. behind any microlens of an integral-photography monitor, between 100 and 300 pixels should appear. In this paper, we make use of an updated version of our algorithm, SPOC 2.0, to alleviate this situation. We propose the application of SPOC 2.0 for the calculation of co…
Formation of real, orthoscopic integral images by smart pixel mapping.
2005
Integral imaging systems are imaging devices that provide 3D images of 3D objects. When integral imaging systems work in their standard configuration the provided reconstructed images are pseudoscopic; that is, are reversed in depth. In this paper we present, for the first time we believe, a technique for formation of real, undistorted, orthoscopic integral images by direct pickup. The technique is based on a smart mapping of pixels of an elemental-images set. Simulated imaging experiments are presented to support our proposal.
A comparative analysis of different spatial sampling schemes: Modelling of SSRB data
2008
Low spatial resolution satellite sensors provide information over relatively large targets with typical pixel resolutions of hundreds of km2. However, the spatial scales of ground measurements are usually much smaller. Such differences in spatial scales makes the interpretation of comparisons between quantities derived from low resolution sensors and ground measurements particularly difficult. It also highlights the importance of developing appropriate sampling strategies when designing ground campaigns for validation studies of low resolution sensors. We make use of statistical modelling of high resolution surface shortwave radiation budget (SSRB) data to look into this problem. A spatial …
A Comparative Study and an Evaluation Framework of Multi/Hyperspectral Image Compression
2009
In this paper, we investigate different approaches for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression approach and two different implementations of 3D approach (full 3D and hybrid) with regards to variations in spatial and spectral dimensions. All approaches are combined with a weighted Principal Component Analysis (PCA) decorrelation stage to optimize performance. For consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR, including eight metrics divided into three families. The results show the weaknesses and strengths of each approach.
Charge loss correction in CZT pixel detectors at low and high fluxes: analysis of positive and negative pulses
2018
Charge losses are typical drawbacks in cadmium–zinc–telluride (CZT) pixel detectors. The effects of these phenomena are strongly related to the interaction point of the photons and are more severe for photon interactions at the inter-pixel gap and near the pixelated anode. In this work, we present some original techniques able to correct charge losses in pixelated CZT detectors at both low and high fluxes. The height, the shape and the arrival time of collected- and induced-charge pulses with both positive and negative polarities are analysed to recover charge losses after the application of charge sharing addition (CSA). Sub-millimetre CZT pixel detectors, fabricated by different manufactu…
Exploring relationships between pixel size and accuracy for debris flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy).
2014
Debris flows are among the most hazardous phenomena in nature, which typically take the form of multiple-occurrence regional landslide events triggered by intense driving inputs such as storms or earthquakes. The main tasks of this study were to verify whether cell-based susceptibility models is capable of predicting debris flow initiations in the Giampilieri catchment (southern Italy) and to explore the relationships between the pixel size of the adopted mapping units in terms of predictive performances of the derived models. The Giampilieri catchment is a small area (10km 2 ) hit by a storm on the 1 st October 2009 which resulted in the triggering of more than one thousand landslides and …
Blood vessels and feature points detection on retinal images
2009
In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The len…