A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object and Texture Classification Using Higher Order Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
Quantization from Bayes factors with application to multilevel thresholding
Pattern Recognition Letters
Pattern recognition using higher-order local autocorrelation coefficients
Pattern Recognition Letters
Image thresholding using Tsallis entropy
Pattern Recognition Letters
High-order statistical texture analysis--font recognition applied
Pattern Recognition Letters
Grading of construction aggregate through machine vision: results and prospects
Computers in Industry - Special issue: Machine vision
Pattern Recognition Letters
Analysis of the spatial distribution of galaxies by multiscale methods
EURASIP Journal on Applied Signal Processing
Markov Random Field Texture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture image retrieval using new rotated complex wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information measures in scale-spaces
IEEE Transactions on Information Theory
Pattern recognition using invariants defined from higher order spectra: 2-D image inputs
IEEE Transactions on Image Processing
Image compression via joint statistical characterization in the wavelet domain
IEEE Transactions on Image Processing
Wavelet domain image restoration with adaptive edge-preserving regularization
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
The Undecimated Wavelet Decomposition and its Reconstruction
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram
Computers in Biology and Medicine
Unsupervised image retrieval framework based on rule base system
Expert Systems with Applications: An International Journal
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We show the potential for classifying images of mixtures of aggregate, based themselves on varying, albeit well-defined, sizes and shapes, in order to provide a far more effective approach compared to the classification of individual sizes and shapes. While a dominant (additive, stationary) Gaussian noise component in image data will ensure that wavelet coefficients are of Gaussian distribution, long tailed distributions (symptomatic, for example, of extreme values) may well hold in practice for wavelet coefficients. Energy (second order moment) has often been used for image characterization for image content-based retrieval, and higher order moments may be important also, not least for capturing long tailed distributional behavior. In this work, we assess second, third and fourth order moments of multiresolution transform - wavelet and curvelet transform - coefficients as features. As analysis methodology, taking account of image types, multiresolution transforms, and moments of coefficients in the scales or bands, we use correspondence analysis as well as k-nearest neighbors supervised classification.