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The orthogonal transforms, such as the discrete Fourier transform (DFT) and Walsh-Hadamard transform (WHT), have widely been used in images processing, data compressing and coding, spatial multiplexing, and other areas [1 11].
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Moments have been widely used in image processing for pattern recognition due to its useful invariance properties such as translation, scale, and rotational invariance [21, 27].
Signal processing in the digital domain is extremely useful for 2D signals such as used in image processing, medical imaging, ultrasound imaging, and so on.
Given k, the allocations Z i follow a spatially correlated process, the Potts model, which has been used in image processing and other spatial applications and involves a positive interaction parameter ψ (similar to an autocorrelation parameter) that influences the degree of spatial dependence of the allocations.
Spatial operations used in image processing are linear operations.
Multiscale representations have been widely used in image processing applications.
They are often used in image processing technology [14, 15].
Local operators, template matching and moments are widely used in image processing.
Total variation method has been widely used in image processing, however, it produces undesirable staircase effect.
Bilateral filtering is a method often used in image processing applications.
In recent years, the nonlocal TV has been successfully used in image processing tasks [6, 7].
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