Foundation cloud picture classification method based on completion local three value model

A technology of local ternary mode and ground-based cloud image, which is applied in the field of image processing, can solve the problem of not being suitable for the natural texture image of ground-based cloud image, and achieve the effect of good noise robustness and classification accuracy

Inactive Publication Date: 2013-10-02
INST OF AUTOMATION CHINESE ACAD OF SCI
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The above classification methods all extract simple texture features from cloud images, which are obviously not s...

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  • Foundation cloud picture classification method based on completion local three value model
  • Foundation cloud picture classification method based on completion local three value model
  • Foundation cloud picture classification method based on completion local three value model

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[0019] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0020] figure 1 It is a flow chart of the ground-based cloud map classification method based on the complete local ternary model proposed by the present invention, such as figure 1 As shown, the method includes the following steps:

[0021] Step 1, for each training ground-based cloud image sample, decompose its local information into two parts: local difference vector and central pixel;

[0022] In this step, the central pixel is easy to obtain. For the local difference vector, assuming a given central pixel point g c and its surrounding P uniformly distributed neighbor pixels g 0 , g 1 ,..., g P-1 , a difference vector can be calculated: [d 0 , d 1 ,...,d P-1 ], where d p =g p -g c , p=0, 1, ..., P-1.

[002...

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Abstract

The invention discloses a foundation cloud picture classification method based on a completion local three value model. The method comprises the following steps that the local information of each training sample is decomposed into local difference value vectors and center pixels; each local difference value vector is decomposed into the products of sign vectors and amplitude vectors; the three-value mode coding is adopted for the sign vectors, the amplitude vectors and the center pixels, and in addition, the rotating unchanged consistency characteristics are respectively calculated; the rotating unchanged consistency characteristics are merged to obtain the final characteristic expression of the training samples; the final characteristic expression of the foundation cloud picture is calculated; and on the basis of the final characteristic expression of the foundation cloud picture and the training samples, the nearest adjacent classifier is adopted to obtain the classification results of the tested foundation cloud picture. The foundation cloud picture classification method has the advantages that the local information of images is considered in three aspects of sign, amplitude and center pixels, the local three-value mode is adopted for coding, and the final coding is carried out to obtain the final characteristic expression of the images, so better noise robustness and classification accuracy can be obtained.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a ground-based cloud image classification method based on a complete local ternary model. Background technique [0002] Clouds are the external manifestations of thermodynamic and dynamic processes in the atmosphere. Their generation and evolution are one of the concrete manifestations of the intricate physical processes that occur in the atmosphere. They not only reflect the movement, stability, and water vapor conditions of the atmosphere at that time, but also can predict the future. The trend of weather changes over a certain period of time. Therefore, cloud observation is an important part of meteorological observation, and accurate acquisition of cloud information is of great significance to weather forecasting, national economy, military support and many other fields. At present, cloud observation is mainly done through ground-based observation and satellite remo...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 王春恒刘爽肖柏华张重
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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