In this work, a robust thresholding algorithm framework based on reconstruction and dimensionality reduction of the three-dimensional (3-D) histogram is proposed with the consideration of the poor anti-noise performan...
详细信息
In this work, a robust thresholding algorithm framework based on reconstruction and dimensionality reduction of the three-dimensional (3-D) histogram is proposed with the consideration of the poor anti-noise performance in existing 3-D histogram-based segmentation methods due to the obviously wrong region division. Firstly, our method reconstructs the 3-D histogram based on the distribution of noisy points which reduce its segmentation performance. Secondly, we transfer the region division in 3D histogram from eight partitions into two parts, thus reducing the searching space of threshold from 3-dimension to 1-dimension, which saves a lot of processing time and memory space. Thirdly, we apply the presented framework to global thresholding algorithms such as Otsu method, minimum error method, and maximumentropy method and so on, and propose corresponding robust global thresholding algorithms. Finally, segmentation result and running time are given at the end of this paper compared with those of 3-D Otsu's method, Otsu method, minimum error method and maximumentropy method. The experimental results show that the presented method has better anti-noise performance and visual quality compared with the above four approaches, and has lower time complexity than 3-D Otsu's method.
Metzgeriaceae are a cosmopolitan family that is particularly diverse in the Neotropics. In Brazil, the species of Metzgeria Raddi preferentially inhabit the coastal ecosystem Atlantic Rain Forest (from northeastern to...
详细信息
Metzgeriaceae are a cosmopolitan family that is particularly diverse in the Neotropics. In Brazil, the species of Metzgeria Raddi preferentially inhabit the coastal ecosystem Atlantic Rain Forest (from northeastern to southern Brazil). For bryophytes, the IUCN distribution criteria are of critical importance to evaluate threat status. In this study, we propose the use of ecological niche modeling methods to estimate the extent of potential occurrence of five Metzgeria species. Herbarium collection data were used to estimate the potential distribution of the species based on the method MAXENT. Understanding the spatial distribution of species is essential for the conservation of biodiversity, and the use of potential distribution models in biogeographic analysis is an important tool for the conservation of rare or endangered species. Modeling the distribution of five Metzgeria species endemic and/or threatened reveals that the species are currently not known from several areas that are, however, predicted to provide suitable environments. From these areas of forest fragments, 52% are under environmental protection, which is very important for the conservation of these species typical of the Atlantic Rain Forest domain. When we intersect this information with future areas of environmental protection, proposed by the Ministry of Environment of Brazil in 2010, we observed that 93% of forest fragments will be protected.
This paper concerns a minimax model to investigate the optimal portfolio selection problem without riskless assets and with or without short sale restriction. A numerical solution to the problem with short sale restri...
详细信息
This paper concerns a minimax model to investigate the optimal portfolio selection problem without riskless assets and with or without short sale restriction. A numerical solution to the problem with short sale restriction is obtained by using the maximum entropy algorithm. For the problem without short sale restriction, we derive a analytical expression for the optimal solution, a sufficient condition for the existence and uniqueness of a nonnegative equilibrium price system, and an explicit formula for the price system. Furthermore, a numerical example is given to show the validity of the method. (C) 2008 Elsevier Inc. All rights reserved.
maximum entropy algorithm for approximating multi-objective smoothless semi-infinite programming is presented. The convergence of the approximating algorithm is obtained in general from the convergence of the series o...
详细信息
maximum entropy algorithm for approximating multi-objective smoothless semi-infinite programming is presented. The convergence of the approximating algorithm is obtained in general from the convergence of the series of entropy functions (such as variational convergence).
Image segmentation is the pre-step of multi-target tracing in Computer Assisted Sperm Motion Analysis System (CASMA). As a special sperm-tracing problem, a fast, automatic, unsupervised segmentation algorithm is requi...
详细信息
ISBN:
(纸本)0819446564
Image segmentation is the pre-step of multi-target tracing in Computer Assisted Sperm Motion Analysis System (CASMA). As a special sperm-tracing problem, a fast, automatic, unsupervised segmentation algorithm is required. In this paper, we utilize four segmentation algorithms to segment three different kinds of sperm images sampled from our actual system. By making an overall comparison between them, a conclusion is reached that the Otsu's maximum between-class variance algorithm is the most suitable for the special sperm microscopic image segmentation and this segmentation algorithm has been successfully applied to our developed system.
A model is suggested for assigning the prior probability of an image in Bayes' theorem which leads to a very general algorithm for image enhancement. Examples of sharpening blurred photographs show how the success...
详细信息
A model is suggested for assigning the prior probability of an image in Bayes' theorem which leads to a very general algorithm for image enhancement. Examples of sharpening blurred photographs show how the success of deconvolution depends on the signal/noise ratio in the degraded images.
暂无评论