Given our choice of the Haar basis, we use a translation-invariant discrete wavelet transformation on the normalized read depth (Coifman and Donoho, 1995) to obtain detailed signal frequency and scale information encapsulated by the approximation and detail coefficients.
Step 2 Threshold detail coefficients: For each level from 1 to N, compare the detail coefficients to threshold values.
More precisely, we design the prediction operators by minimizing the variance of the detail coefficients.
At each temporal resolution, two categories of coefficients are obtained: approximation coefficients and detail coefficients.
In [5], vertical detail coefficients of Haar undecimated wavelet transform were thresholded to identify RoIs.
An approximate entropy (ApEn) was extracted from the approximation and the detail coefficients.
The detail coefficients of the "einst" image are optimized by minimizing their ℓ2-norm.
(5) Denoise the detail coefficients using 3D WNS thresholding technique (see Section 2.4).
The fault time tags are extracted directly from the wavelet detail coefficients.
The adaptive threshold is based on a real-time sorting process which calculates the median of the detail coefficients.
The Bayes least squares estimator is used to obtain the denoised detail coefficients from the noisy image decomposition.
