Abstract
Texture is an important characteristic of the appearance of objects in natural scenes and is a crucial cue in visual perception. It plays an important role in computer vision, graphics, and image encoding. Understanding texture is an essential part of understanding human vision.
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Notes
- 1.
We assume the histogram of each sub-band I(α) is normalized such that \(\sum _i H_i^{(\alpha )} =1\), and therefore all the \(\{\lambda _i^{(\alpha )}, i=1, \ldots , L\}\) computed in this algorithm have one extra degree of freedom for each α, i.e., we can increase \(\{\lambda _i^{(\alpha )}, i=1, \ldots , L\}\) by a constant without changing p(I; ΛK, SK). This constant will be absorbed by the partition function Z( ΛK).
- 2.
We assume D →Z2 in the sense of van Hove, i.e., the ratio between the boundary and the size of D goes to 0.
- 3.
We hope that the notation h(I) = h will not confuse the reader. The h on the left is a function of I for extracting statistics, while the h on the right is a specific value of the statistics.
- 4.
In the i.i.d. case, \(q({\mathbf {I}}_{{D}_0}; h)\) is both the marginal distribution and the conditional distribution of q(I; h), while in random fields, we only consider the conditional distribution.
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Zhu, SC., Wu, Y.N. (2023). Textures. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-96530-3_3
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