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Accounting for the effect of spatially varying intensity distortions, the residual complexity (RC) is used as the similarity metric.
Although residual complexity can solve this problem in certain situations, relative modification of the parameter can generate dramatically different results.
The experimental results clearly indicated that the proposed approach has achieved more accurate and robust performance than mutual information, residual complexity and Jensen Tsallis.
By introducing a specifically designed exponential weighting function to the residual term in residual complexity, the proposed similarity measure performed well due to automatically weighting the residual image between the reference image and the warped floating image.
local residual complexity.
global residual complexity.
Similar(48)
This allows to evaluate the local residual with a complexity of O p4) and O p5) for affine and non-affine elements, respectively.
The criterion in (85) reflects the tradeoff between the variance of the residual and the complexity of the model.
The second step of WM-MOGA finds the optimal subset of endmembers in terms of unmixing residual error and complexity, by using a multi-objective genetic algorithm (MOGA) [17, 18, 20] to calculate the Pareto front of non dominated solutions, as defined in the introduction section, P = E 1,..., E q ⊆ P E WM, where P E WM is the power-set of E WM.
These criteria are all based on the goodness of fit (sum of squared differences between measured and estimated data, also termed residuals) and the complexity of the model (number of fit parameters).
The AIC includes both the estimated residual error and model complexity in one statistic.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com