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where the functions Lu, Co, and St describe the luminance, contrast, and structure measures between two image matrices, respectively.
The reconstructed images were consistent with 80 × 80 image matrices and had a spatial resolution of 0.8 mm.
Further, vectorizing the image matrices very often shows a singularity problem during the inversion of scatter matrices in case of LDA-based training.
Unlike probabilistic CCA which converts the image samples into the vectors, our method uses the original image matrices for data representation.
Most of the existing PCA- and LDA-based classification methods while applied to the images consider the transformation of image matrices to image vectors.
For an image matrix of 2563, the voxel size was 120 μm on a side, whereas image matrices of 1283 and 643 had voxel sizes of 200 and 400 μm, respectively.
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The image matrix was 512*512 pixels.
(4) Output the new image matrix Y. .
Convert the bit sequence into an image matrix. 5.
This matrix consists of as many elements as there are pixels in the image matrix.
Here, is the watermark embedded DET matrix, and is the watermarked image matrix.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com