A Raman Spectral Image Unmixing Method Based on Non-negative Matrix Adjacency
A Raman spectroscopy, non-negative matrix technology, applied in the field of image processing, can solve problems such as unsatisfactory assumptions, and achieve the effect of improving noise resistance and stability
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Embodiment 1
[0032] Based on the rank 1-NMU algorithm, the invention proposes a non-negative matrix proximity algorithm for sparse graph relations.
[0033] The basic rank 1-NMU algorithm can be formulated as an optimization problem as shown in the following formula:
[0034]
[0035] in: is the F norm. matrix is the image data matrix, matrix u and matrix v are row vectors with length m and length n respectively.
[0036] Such as figure 1 As shown, the present invention is based on the Raman spectral image unmixing method that the non-negative matrix is adjacent, comprises the following steps:
[0037] (1) Perform noise reduction and defluorescence processing on the Raman image to obtain processed image data.
[0038] (2) For the pixels in the image data, calculate the weight between the pixels according to the following formula:
[0039]
[0040] where: m i and m j are any two pixels in the image data, and σ is the kernel width of the thermal kernel function.
[0041] (...
Embodiment 2
[0065] Below we take the structural components of the tea plant cell wall as an example to describe the specific implementation of the method proposed by the present invention.
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