International Journal of Computer Vision
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
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Empirical evaluation of dissimilarity measures for color and texture
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Matching and retrieval based on the vocabulary and grammar of color patterns
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Adaptive perceptual color-texture image segmentation
IEEE Transactions on Image Processing
A GPU implementation of a structural-similarity-based aerial-image classification
The Journal of Supercomputing
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The development of objective texture similarity metrics for image analysis applications differs from that of traditional image quality metrics because substantial point-by-point deviations are possible for textures that according to human judgment are essentially identical. Thus, structural similarity metrics (SSIM) attempt to incorporate "structural" information in image comparisons. The recently proposed structural texture similarity metric (STSIM) relies entirely on local image statistics. We extend this idea further by including a broader set of local image statistics, basing the selection on metric performance as compared to subjective evaluations. We utilize both intra- and inter-subband correlations, and also incorporate information about the color composition of the textures into the similarity metrics. The performance of the proposed metrics is compared to PSNR, SSIM, and STSIM on the basis of subjective evaluations using a carefully selected set of 50 texture pairs.