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Infrared imaging volume cloud detection method based on fractal dictionary learning

A dictionary learning and infrared imaging technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low recognition accuracy and interference, and achieve the effects of improved efficiency, easy implementation, and high detection accuracy

Active Publication Date: 2019-08-02
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0004] The purpose of the present invention is to: in order to solve the problem that the false alarm source can interfere with the detection of the target and cause the low precision of target detection and recognition in ground detection, a kind of infrared imaging cirrus cloud detection method based on fractal dictionary learning is provided

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  • Infrared imaging volume cloud detection method based on fractal dictionary learning
  • Infrared imaging volume cloud detection method based on fractal dictionary learning
  • Infrared imaging volume cloud detection method based on fractal dictionary learning

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Embodiment 1

[0061] A kind of infrared imaging cirrus detection method based on fractal dictionary learning that the preferred embodiment of the present invention provides, such as figure 1 shown, including the following steps:

[0062] Step 1. Input an infrared image of cirrus clouds to be detected with a pixel size of m×n, such as image 3 , and filter and denoise it to obtain the preprocessed cirrus cloud image. The specific method of filtering and denoising the infrared image of cirrus clouds is as follows: sort the pixels in the neighborhood of each pixel point on the infrared image of cirrus clouds according to the gray value from small to large, and obtain the gray value of each pixel point neighborhood. Median value, and assign the obtained median value to the corresponding pixel to obtain a preprocessed cirrus cloud image with a pixel size of m×n. Image denoising is performed by median filtering method, which can preserve image edges well.

[0063] Step 2. Obtain the Hurst expo...

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Abstract

The invention discloses an infrared imaging volume cloud detection method based on fractal dictionary learning in technical field of infrared image processing which aims to solve the problem that a large amount of false alarm sources with very high radiation energy exist in an infrared imaging wave band, and the false alarm sources can interfere the detection of a target. The method for solving the false alarm source interference target detection problem comprises the following specific steps: 1, inputting a to-be-detected volume cloud infrared image, and carrying out filtering and denoising on the to-be-detected volume cloud infrared image to obtain a preprocessed volume cloud image; 2, acquiring a Hurst index value of the preprocessed volume cloud image; 3, solving a random fractal imagebased on the Hurst index value obtained in the step 2 and a rhombus-square subdivision method, and constructing an over-complete dictionary D based on the random fractal image; 4, performing sparse coding and dictionary updating on the over-complete dictionary D by using a K-SVD algorithm to obtain a sparse representation image; and 5, performing morphological filtering and image segmentation processing on the sparse representation image to obtain a detection result image. The method is easy to implement, high in detection effect accuracy and short in algorithm calculation time.

Description

technical field [0001] The invention relates to the technical field of infrared image processing, in particular to an infrared imaging cirrus cloud detection method based on fractal dictionary learning. Background technique [0002] Infrared satellites are an important part of the earth observation and remote sensing system, and play an important role in missile interception and early warning. Due to the infrared satellite imaging system, there are false alarm sources with high radiation energy in the infrared imaging band, mainly natural landscapes, such as snow-capped mountains, high-altitude cirrus clouds, frozen rivers and other high-radiation terrain or phenomena, and the target in the infrared image The performance is similar, with a higher gray scale, so it may cause false alarms in the remote sensing early warning system. [0003] Through the study of image texture, it is found that natural landscapes usually have the characteristics of irregular shape, rough gray s...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06T7/12G06T7/90
CPCG06T7/0002G06T7/12G06T7/90G06T2207/10048G06T2207/10032G06T2207/20081G06T2207/20036G06T2207/30181G06T5/70
Inventor 吕昱霄彭真明曹思颖刘雨菡彭凌冰杨春平宋立张鹏飞王光慧曹兆洋高原
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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