Lightweight Probabilistic Texture Retrieval

R. Kwitt, A. Uhl
2010 IEEE Transactions on Image Processing  
This article contemplates the framework of probabilistic image retrieval in the wavelet domain from a computational point of view. We not only focus on achieving high retrieval rates, but also discuss possible performance bottlenecks which might prevent practical application. We propose a novel retrieval approach which is motivated by previous research work on modeling the marginal distributions of wavelet transform coefficients. The building blocks of our work are the Dual-Tree Complex Wavelet
more » ... Transform and a number of statistical models for the coefficient magnitudes. Image similarity measurement is accomplished by using closed-form solutions for the Kullback-Leibler divergences between the statistical models. We provide an in-depth computational analysis regarding the number of arithmetic operations required for similarity measurement and model parameter estimation. The experimental retrieval results on a widely-used texture image database show that we achieve competitive retrieval results at low computational cost.
doi:10.1109/tip.2009.2032313 pmid:19758865 fatcat:onobouk6hnfevb5zqv57etfuz4