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It is pertinent to notice that a large number of signal issued representations could be converted in image representations.
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Adaptive sampling has become popular in image representation, among which triangular meshes have gained much interest.
Unlike traditional separable transforms, the resulting 2D subbands have flexible directional-selectivity which is highly expected in image representation.
Triangular meshes have gained much interest in image representation and have been widely used in image processing.
This knowledge comes from the meaning of LOW, MEDIUM, HIGH moments' amplitudes, orders and repetitions in image representation.
Different adaptive sampling methods and mesh strategies have been applied in image representation by other researchers as summarized in Section 1.
One of our objectives in this paper is to build the framework for AMA in image representation that can take different metric tensors for different needs in image processing.
Motivated by the co-occurrence concept such as in Co-HOG [29 31] and joint haar-like features [30], Nosaka et al. [17, 18] proposed to integrate context information (i.e., spatial and orientation) into the conventional LBP for achieving high descriptive capacity in image representation; the similar extension of LBP for integrating context information also can be seen in the recent work [19].
We note that the texture and the shape features are widely used in image representation.
The performance of content-based image retrieval relies on the separation of samples and clusters in the feature space, training sample size, diversity, and on the balance in image representation among categories.
Instead, given a pair of images that are related by a non-uniform image deformation, the lack of affine covariance implies that there will be a systematic bias in the image representations derived from such Gabor functions, corresponding to the difference between the backprojected Gabor functions in the two image domains.
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