SAR Image Retrieval Method Based on Sparse Coding Classification

A sparse coding and image retrieval technology, applied in the field of SAR image retrieval based on sparse coding, can solve the problems of high time complexity and low classification accuracy.

Active Publication Date: 2017-05-10
XIDIAN UNIV
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Problems solved by technology

These methods can quickly and accurately classify images, but because model building and learning are required during processing, the time complexity of the method is high; unsupervised image classification methods include cluster analysis and fuzzy cluster analysis
The implementation of these two methods is faster, but the classification accuracy is lower

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  • SAR Image Retrieval Method Based on Sparse Coding Classification
  • SAR Image Retrieval Method Based on Sparse Coding Classification
  • SAR Image Retrieval Method Based on Sparse Coding Classification

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Embodiment Construction

[0085] Such as figure 1 shown. A SAR image retrieval method based on sparse coding classification, at least including process steps:

[0086] Step 101: start the SAR image retrieval method based on sparse coding classification;

[0087] Step 102: Select training images in the SAR image library, and read these images. The size of each image selected in this patent is 256×256, and it is preprocessed by using the refined Lee filtering method to reduce the impact of coherent speckle noise on the image. The impact of classification results, the window size of the filter is set to 7×7;

[0088] Step 103: Use the gray level co-occurrence matrix method to extract features from the preprocessed training image, set the value of the direction θ to be 0°, 45°, 90°, 135°, that is, east-west, northeast-southwest, south —North, southeast-northwest 4 directions; 5 features are selected for each direction, namely energy, entropy, contrast, local similarity and correlation. Therefore, 20 fe...

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Abstract

The invention provides an SAR image search method based on sparse coding classification. The SAR image search method aims at the defects of an existing image search system and method. Through extraction of characteristics and construction of an over-complete dictionary, solution is carried out through sparse representation based on a dual Memetic algorithm, a sparse representation classifier is trained, the classification process with supervision can be achieved in the classification process, the sparse solution with global optimum can be solved fast, and then search results are output from high to low according to similarity. When the problem of image classification is solved, the method achieves the good improvement effect on classification accuracy, search content similarity, calculating complexity and result robustness.

Description

technical field [0001] The invention belongs to the field of SAR image processing, and relates to a SAR image retrieval method based on sparse coding, which can accurately classify SAR images and realize retrieval, and effectively reduce the influence of coherent speckle noise on SAR image classification results. Background technique [0002] Synthetic Aperture Radar—Synthetic ApertureRadar, is an effective means of earth observation from space, and has been widely used in military reconnaissance, landform observation, urban planning, etc. With the improvement of SAR imaging technology in recent years, the number of SAR images has shown explosive growth. Considering the characteristics of large amount of data and large noise in SAR images, how to efficiently and accurately retrieve the required images from the massive SAR image database has become an urgent problem to be solved. [0003] With the development of information technology, the image retrieval method has changed ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/583
Inventor 焦李成马文萍高晓莹尚荣华杨淑媛马晶晶
Owner XIDIAN UNIV
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