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Principal axes analysis of symbolic histogram variables
Statistical Analysis and Data Mining: The ASA Data Science Journal, 2015We present a new method to perform a principal axes analysis of symbolic histogram variables. In the symbolic data analysis framework, several Histogram Principal component Analysis (Histogram PCA) have been proposed. Some approaches focus on the relationships between some specific features of histograms such as the means or the quantiles.
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Fuzzy Thresholding and Histogram Analysis
2003This chapter provides a comprehensive discussion of several thresholding techniques that employ the concept of the measure of fuzziness. The basic concepts and ideas of the measures of fuzziness are introduced. A unified description of the fuzzy thresholding methods based on the measure of fuzziness is given.
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Highlight Detection by 2D-Histogram Analysis
Conference on Colour in Graphics, Imaging, and Vision, 2004openaire +2 more sources
A Novel 3-D Color Histogram Equalization Method With Uniform 1-D Gray Scale Histogram
IEEE Transactions on Image Processing, 2011Byung-Uk Lee, Sejung Yang
exaly
Bi-histogram equalization using modified histogram bins
Applied Soft Computing Journal, 2017Nor Ashidi Mat Isa
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Brightness preserving histogram equalization with maximum entropy: a variational perspective
IEEE Transactions on Consumer Electronics, 2005Zhongfu Ye
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Multiresolution histograms and their use for recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004Michael D Grossberg +2 more
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A Dynamic Histogram Equalization for Image Contrast Enhancement
IEEE Transactions on Consumer Electronics, 2007Mohammad Abdullah-Al-Wadud +2 more
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