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Coarse edge detection method for heterogeneous images based on fast kernel space fuzzy clustering

A fuzzy clustering and heterogeneous image technology, applied in the field of image processing, can solve problems such as ineffective extraction

Inactive Publication Date: 2015-09-30
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

The method of this patent can extract the rough edges of visible light and infrared images well, but for SAR images and actual noise-containing heterogeneous images, this method cannot effectively extract

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  • Coarse edge detection method for heterogeneous images based on fast kernel space fuzzy clustering
  • Coarse edge detection method for heterogeneous images based on fast kernel space fuzzy clustering
  • Coarse edge detection method for heterogeneous images based on fast kernel space fuzzy clustering

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Embodiment Construction

[0045] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0046] refer to figure 1 , a coarse edge detection method for heterogeneous images based on fast kernel space fuzzy clustering, including the following steps:

[0047] 1) Calculate the grayscale and texture feature values ​​of each pixel in the image, and construct a two-dimensional feature space;

[0048]According to the analysis and research on the imaging principle of heterogeneous images and the characteristics of rough edges, grayscale is the most basic feature to characterize images, and texture reflects the spatial distribution of image grayscale patterns, which better takes into account the macroscopic information and microscopic information information, so grayscale and texture features are selected to describe heterogeneous images; the characteristics of grayscale and texture features are comprehensively analyzed, and the g...

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Abstract

The invention discloses a different source image rough edge test method based on rapid nuclear spatial fuzzy clustering. Rough edge test method of rapid nuclear spatial possibility fuzzy C-mean clustering based on grey level and texture is put forward due to the fact that features of inter-object rough edges of different source images which have similarity are analyzed. A possibility fuzzy C-mean clustering algorithm to a certain extent overcomes the defects that a fuzzy C-mean is sensitive to noise data and a possibility C-mean is prone to producing conforming clustering. Furthermore, robustness is further improved through linearly separable idea of a nuclear space, the idea is subtracted due to the fact that data in data analysis is introduced, feature spatial datasets involved in iteration are compressed, and real-time performance is greatly improved. The different source image rough edge test method based on the rapid nuclear spatial fuzzy clustering has the advantages of rapidly and accurately drawing the different source rough edges of actual existing noises and building a solid foundation for matching the different source images.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for detecting rough edges of heterogeneous images based on fast kernel space fuzzy clustering. Background technique [0002] With the emergence of sensors with different imaging principles, heterogeneous image matching technology has become a key technology in the fields of remote sensing, navigation and guidance. However, there are still many difficulties in the research of heterogeneous image matching, especially the large differences in the imaging mechanism of heterogeneous images (such as optical and synthetic aperture radar (SAR) images), and the large differences in wavelength bands (such as visible light and long-wave infrared (IR) images). It is difficult to better obtain the common features of the image in terms of grayscale, brightness, color and other characteristics. According to the analysis of heterogeneous image imaging principles and typical heterogeneou...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 赵妍徐贵力王彪郭瑞鹏
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS