Image classification method based on an observation matrix transformation dimension
A technology of observation matrix and classification method, applied in instruments, character and pattern recognition, computer parts, etc., can solve the problems of unfavorable storage and transmission, increased calculation amount, large amount of digital signal data, etc., and achieve the effect of improving model efficiency
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[0045] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0046] Such as figure 1 As shown, this embodiment provides an image classification method based on the transformation dimension of the observation matrix, including the following steps:
[0047] (1) Use perceptual compression to sparsely encode images to obtain a data set composed of low-dimensional images, and divide the data set containing labels into training set and test set with a ratio of 8:2.
[0048] Methods for sparsely coding images using perceptual compression include sparse representation of images, image compression sampling, and image reconstruction.
[0049] (1-1) Image sparse representation is:
[0050] Express the original signal x on a set of sparse basis Ψ:
[0051] x=Ψs
[0052] Among them, x is the original signal, its size is N×1, Ψ is a set of sparse basis, and s is the sparse coefficient.
[0053] s is an N×1 column vector c...
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