Image block clustering method based on Fourier spectrum characteristics

A Fourier spectrum and clustering method technology, applied in the field of image block clustering based on Fourier domain spectral structure and directional characteristics, can solve the problem of limited clustering refinement degree, image block similarity, lack of collaborative metrics, etc. problem, to achieve the effect of good clustering results and good clustering effect

Inactive Publication Date: 2017-06-20
XIAMEN UNIV
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Problems solved by technology

However, the existing image block clustering methods usually only consider one or two feature items in the spatial domain, and lack a collaborative metric composed of multiple feature information, which greatly limits the refinement of clustering and the accuracy of various types of clustering. Similarity of image blocks

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  • Image block clustering method based on Fourier spectrum characteristics
  • Image block clustering method based on Fourier spectrum characteristics
  • Image block clustering method based on Fourier spectrum characteristics

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Embodiment Construction

[0026] The present invention will be further described below through specific embodiments.

[0027] According to Fourier theory, any signal can be expressed as the sum of a series of sine functions. A one-dimensional sine function has frequency, phase, and amplitude, and a two-dimensional sine function also has a direction. The frequency reflects the change of the signal strength in the space domain, the amplitude corresponds to the signal contrast in the space domain, and the phase represents the displacement of the frequency relative to the original signal. The direction of each point in the two-dimensional spectrum is perpendicular to the direction of image intensity variation in the spatial domain. Since the new image structure information contained in the phase spectrum is not much, only the amplitude spectrum of the image block is considered in the present invention. We generally center the spectrum in the Fourier domain, that is, move the zero-frequency point (DC comp...

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Abstract

The invention discloses an image block clustering method based on Fourier spectrum characteristics, and the method comprises the steps: firstly carrying out two-dimensional fast Fourier transform of each image block, so as to obtain an amplitude spectrum corresponding to a Fourier domain; secondly setting the direction with the maximum frequency energy of the amplitude spectrum as a first direction D, enabling the number of a main spectrum line direction as the structural complexity C of image blocks, calculating a frequency component, and setting a frequency component mark; finally carrying out the clustering according to the first direction D of each image block, the structural complexity C and the frequency component mark. The method employs the frequency spectrogram to extract the structural complexity, the structural directivity and the frequency component distribution, so as to design a synergetic similarity measurement standard combining the structure, directivity and contrast characteristics and achieve the quick and fine clustering of image block data sets.

Description

technical field [0001] The invention relates to the field of image processing and pattern recognition, and relates to the construction and learning of an adaptive dictionary in the inverse problem of image processing, and in particular to an image block clustering method based on Fourier domain spectrum structure and direction characteristics. Background technique [0002] In image processing and pattern recognition, the inverse problem of image processing based on image blocks is very common, including image denoising, deblurring, super-resolution reconstruction and image restoration. The solution to this type of problem usually uses a learning algorithm to learn the signal of the image block from the training sample data set, or approximates the signal of the image block by a set of bases in the dictionary. Therefore, the performance of the training sample data set or the dictionary directly determines the reconstruction result. However, the local content of different reg...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/08G06F2218/12G06F18/23213
Inventor 包立君叶富泽
Owner XIAMEN UNIV
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