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Global optimization of histograms [PDF]
Proceedings of the 2001 ACM SIGMOD international conference on Management of data, 2001 Histograms are frequently used to represent the distribution of data values in an attribute of a relation. Most previous work has focused on identifying the optimal histogram (given a limited number of buckets) for a single attribute independent of other attributes/histograms . In this paper, we propose the idea of
Hui Jin +3 more
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The computation of the Bhattacharyya distance between histograms without histograms
2010 2nd International Conference on Image Processing Theory, Tools and Applications, 2010In this paper we present a new method for fast histogram computing and its extension to bin to bin histogram distance computing. The idea consists in using the information of spatial differences between images, or between regions of images (a current and a reference one), and encoding it into a specific data structure: a tree.
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On Histograms and Isosurface Statistics
IEEE Transactions on Visualization and Computer Graphics, 2006In this paper, we show that histograms represent spatial function distributions with a nearest neighbour interpolation. We confirm that this results in systematic underrepresentation of transitional features of the data, and provide new insight why this occurs.
Hamish Carr, B. Denby, Brian R. Duffy
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International Journal of Radiation Oncology*Biology*Physics, 1991
A plot of a cumulative dose-volume frequency distribution, commonly known as a dose-volume histogram (DVH), graphically summarizes the simulated radiation distribution within a volume of interest of a patient which would result from a proposed radiation treatment plan.
William B. Harms +6 more
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A plot of a cumulative dose-volume frequency distribution, commonly known as a dose-volume histogram (DVH), graphically summarizes the simulated radiation distribution within a volume of interest of a patient which would result from a proposed radiation treatment plan.
William B. Harms +6 more
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Parallel Histogram Calculation for FPGA: Histogram Calculation
2016 IEEE 6th International Conference on Advanced Computing (IACC), 2016In this paper, an architecture is proposed to calculate the histogram of image. Which is faster than the previousserial methods, this architecture achieves the parallelism butneeds the enough resources and gives the better performance. If, resources is not an issue then this is one of the best methodfor histogram calculation in FPGA (Field Programmable
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Bi-histogram equalization using modified histogram bins
Applied Soft Computing, 2017Display Omitted The proposed BHEMHB improves conventional histogram equalization.Histogram segmentation enables mean brightness preservation.Histogram modification reduces domination effect of high-frequency histogram bins.BHEMHB is tested using standard and cervical cell images.Statistical analyses reveal improvement in entropy, PSNR and AMBE ...
Jing Rui Tang, Nor Ashidi Mat Isa
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2007
Histograms are data objects that are commonly used to characterize media objects like image, video, audio etc. Symbolic Data Analysis (SDA) is a field which deals with extracting knowledge and relationship from such complex data objects. The current research scenario of SDA has contributions related to dimensionality reduction of interval kind data ...
R. Pradeep Kumar, P. Nagabhushan
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Histograms are data objects that are commonly used to characterize media objects like image, video, audio etc. Symbolic Data Analysis (SDA) is a field which deals with extracting knowledge and relationship from such complex data objects. The current research scenario of SDA has contributions related to dimensionality reduction of interval kind data ...
R. Pradeep Kumar, P. Nagabhushan
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, 2003 In this lecture we first discuss “static” single- and multiple-histogram reweighting methods and then move on to “dynamic” updating methodologies related to histogramming. Specifically we will consider the multicanonical approach and tempering methods. The methods are illustrated with applications to systems exhibiting first-order phase transitions and
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2012
In this chapter, you will learn how to make sense of a list of numbers by visually interpreting the histogram picture whose bars rise above the number line (so that tall bars easily show you where lots of data are concentrated) answering the following kinds of questions: One: What values are typical in this data set?
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In this chapter, you will learn how to make sense of a list of numbers by visually interpreting the histogram picture whose bars rise above the number line (so that tall bars easily show you where lots of data are concentrated) answering the following kinds of questions: One: What values are typical in this data set?
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Fuzzy Sets and Systems, 2000
The construction of a generalized histogram displaying the distribution of a sample of n fuzzy numbers into k fuzzy intervals is suggested. It is shown that the classical histogram representing a partition of a sample of crisp numbers into crisp intervals is a special case of the generalized histogram.
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The construction of a generalized histogram displaying the distribution of a sample of n fuzzy numbers into k fuzzy intervals is suggested. It is shown that the classical histogram representing a partition of a sample of crisp numbers into crisp intervals is a special case of the generalized histogram.
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