Image feature binary coding representation method based on structure optimal subspace learning
A technology of subspace learning and image features, applied in image coding, image data processing, instruments, etc.
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[0174] This embodiment includes the following parts:
[0175] Step 1, data preprocessing.
[0176] The workflow diagram of the data preprocessing steps is as follows: figure 2 shown.
[0177] The purpose of the feature representation and learning algorithm based on binary coding is to give a training set containing N samples where x i Represents the d-dimensional feature vector corresponding to each training sample, and uses a learning algorithm to find a set of suitable hash functions Each hash function encodes a feature vector, mapping it to a one-bit binary number. Then, learn a set of hash function combinations G(x)=[h 1 (x), h 2 (x),...,h g (x)], and use it to encode each feature Get a low-dimensional binary string, where g<
[0178] now assume It is a set of...
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Abstract
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