DTCWTDual-Tree Complex Wavelet Transform
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References in periodicals archive ?
To assess the performance of the proposed method, the GP [10], DTCWT [12], CVT [18], NSCT [19], NSST [20], SR-OMP [23], and NSCT-SR-OMP [25, 26] based fusion methods are implemented for comparison.
To assess the performance of the proposed method, the GP, DTCWT, CVT, NSCT, NSST, SR-OMP, and NSCT-SR-OMP based fusion methods are implemented for comparison.
For our proposed approach, we extract the DTCWT [16] coefficients from the input MRI images.
The DTCWT coefficients of input images are shift invariant; they do not change when an image is shifted in time or space.
The best algorithms for DIII till now are FRFT + WTT + TSVM [282] and DTCWT + VE + TSVM [285] with a detection accuracy of 99.57%.
Our contribution aims to introduce a novel method for AD detection with higher accuracy than state-of-the-art methods, on the basis of DTCWT, PCA, and ANN technique.
The proposed method consists of three important stages, namely, feature extraction using DTCWT, feature dimensionality reduction using PCA, and classification using feed-forward artificial neural network.
Section 2 deals with the preliminary details of Q-shift DTCWT. Section 3 describes the proposed approach of image fusion.
In 1999, Kingsbury proposed a new form of DTCWT, which can both keep the advantages of CWT and achieve the function of perfect reconstruction [8].
The obtained fused images from DWT, FDCT, DTCWT, NSCT-1, and NSCT-2 are shown in Figures 4(c1)4(g1) and 4(c2)-4(g2), respectively.
The comparison of DWT, FDCT, DTCWT, NSCT-1, NSCT-2, and proposed method, shown in Figures 4(c3)-4(h3), clearly implies that the fusion result of the proposed method has better quality and contrast in comparison to other methods.
A pair of frames from input image sequences and four fused images produced by DWT, 3D DWT, 3D DTCWT, and proposed 3DShearlet-3DPCNN are shown in Figure 4.