Sum and Difference Histograms for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduced Multidimensional Co-Occurrence Histograms in Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Mathematics and Computers in Simulation
The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Supervised Texture Classification Using Characteristic Generalized Gaussian Density
Journal of Mathematical Imaging and Vision
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
IEEE Transactions on Multimedia
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Image compression via joint statistical characterization in the wavelet domain
IEEE Transactions on Image Processing
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
Multiscale image segmentation using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Texture classification using refined histogram
IEEE Transactions on Image Processing
Contourlet-based texture classification with product bernoulli distributions
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Statistical contourlet subband characterization for texture image retrieval
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
A performance evaluation of gradient field HOG descriptor for sketch based image retrieval
Computer Vision and Image Understanding
Statistical texture retrieval in noise using complex wavelets
Image Communication
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The modeling of image data by a general parametric family of statistical distributions plays an important role in many applications. In this paper, we propose to adopt the three-parameter generalized Gamma density (GΓD) for modeling wavelet detail subband histograms and for texture image retrieval. The advantage of (GΓD) over the existing generalized Gaussian density (GGD) is that it provides more flexibility to control the shape of model which is critical for practical histogram-based applications. To measure the discrepancy between (GΓD)s, we use the symmetrized Kullback-Leibler distance (SKLD) and derive a closed form for the SKLD between (GΓD)s. Such a distance can be computed directly and effectively via the model parameters, making our proposed scheme particularly suitable for image retrieval systems with large image database. Experimental results on the well-known databases reveal the superior performance of our proposed method compared with the current existing approaches.