Ten lectures on wavelets
Pyramid-based texture analysis/synthesis
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Texture Classification Using Windowed Fourier Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatial Size Distributions: Applications to Shape and Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
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
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
A random set view of texture classification
IEEE Transactions on Image Processing
Rotation-invariant texture retrieval with gaussianized steerable pyramids
IEEE Transactions on Image Processing
Wavelet-Based Feature Extraction for Handwritten Numerals
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Lightweight probabilistic texture retrieval
IEEE Transactions on Image Processing
Statistical texture retrieval in noise using complex wavelets
Image Communication
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This paper presents a novel texture descriptor based on the wavelet transform. First, we will consider vertical and horizontal coefficients at the same position as the components of a bivariate random vector. The magnitud and angle of these vectors are computed and its histograms are analyzed. This empirical magnitud histogram is modelled by using a gamma distribution (pdf). As a result, the feature extraction step consists of estimating the gamma parameters using the maxima likelihood estimator and computing the circular histograms of angles. The similarity measurement step is done by means of the well-known Kullback-Leibler divergence. Finally, retrieval experiments are done using the Brodatz texture collection obtaining a good performance of this new texture descriptor. We compare two wavelet transforms, with and without downsampling, and show the advantage of the second one, which is translation invariant, for the construction of our texture descriptor.