  Detections of gravitational-wave signals from compact binary coalescences
have enabled us to study extreme astrophysical phenomena and explore
fundamental physics. A crucial requisite for these studies is to have accurate
signal models with characteristic morphologies, which have been challenging for
many decades, and researchers are still endeavoring to incorporate important
physics. Therefore, morphology-independent methods have been developed for
identifying a signal and its reconstruction. The reconstructed signal allows us
to test the agreement between the observed signal and the waveform posterior
samples from parameter estimation. These methods model observed signals using a
nearly orthogonal wavelet basis in the frame of continuous wavelet
transformation. Here, we propose log-uniform scales to construct the wavelets,
which are are highly redundant (nonorthogonal) compared to the conventional
octave scales but more efficient for reconstructing the signals at high
frequencies. And we introduce a semi-model-dependent reconstruction method
using the posterior samples of the events, where we model the signal using
Gabor-Morlet wavelets with log-uniform scales. We demonstrate the ability to
detect deviation using a numerical simulation of an eccentric binary black hole
merger, where the signal in the data does not belong to the search template
waveform manifold. Finally, we apply this method to each binary black hole
merger event in GWTC-1. We have found that the signal produced by the GW150914
event has 96% agreement with the waveform posterior samples. As the detector
sensitivity improves and the detected population of black hole mergers grows,
we expect the proposed method will provide even stronger tests.
