Remote sensing image classification method based on multi-feature fusion

A multi-feature fusion, remote sensing image technology, applied in the field of image recognition, can solve problems such as no longer applicable, and achieve the effect of improving classification accuracy, high classification accuracy and high precision

Active Publication Date: 2012-08-01
HOHAI UNIV
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Obviously, if the same feature is used to classify d

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  • Remote sensing image classification method based on multi-feature fusion
  • Remote sensing image classification method based on multi-feature fusion
  • Remote sensing image classification method based on multi-feature fusion

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Embodiment Construction

[0033] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0034]Considering that the salient features of each type of image are not consistent, and the misclassification of different features is also different, the present invention proposes a multi-feature fusion remote sensing image classification method, using the bag of visual words feature, color histogram feature and texture The features are classified separately, and voting is performed according to the classification results obtained by each feature, and finally the classification result after multi-feature fusion is obtained; the present invention further improves the visual bag-of-words model, by analyzing the significant word feature information of different scene classes weighting, which increases the similarity of a single image to the overall class. Some individual differences are obvious, but semantically similar images have achieved a good clas...

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Abstract

The invention discloses a remote sensing image classification method based on multi-feature fusion, which includes the following steps: A, respectively extracting visual word bag features, color histogram features and textural features of training set remote sensing images; B, respectively using the visual word bag features, the color histogram features and the textural features of the training remote sensing images to perform support vector machine training to obtain three different support vector machine classifiers; and C, respectively extracting visual word bag features, color histogram features and textural features of unknown test samples, using corresponding support vector machine classifiers obtained in the step B to perform category forecasting to obtain three groups of category forecasting results, and synthesizing the three groups of category forecasting results in a weighting synthesis method to obtain the final classification result. The remote sensing image classification method based on multi-feature fusion further adopts an improved word bag model to perform visual word bag feature extracting. Compared with the prior art, the remote sensing image classification method based on multi-feature fusion can obtain more accurate classification result.

Description

technical field [0001] The invention relates to an image classification method, in particular to a remote sensing image classification method based on multi-feature fusion, and belongs to the technical field of image recognition. Background technique [0002] With the rapid development of remote sensing and information technology, the amount of remote sensing image data that can be obtained every day is increasing at an alarming rate. In the face of massive remote sensing data, how to use computers to automatically classify images into different semantic categories according to the way people understand has become a challenging problem. In the semantic content of computer vision research, the scene category of an image not only contains people's overall understanding of an image, but also provides a basis for further recognition of other content in the image. Therefore, image scene classification has become a hot issue in the field of computer vision and multimedia informat...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 李士进刘帅邹阳姜玲玲洪凡荣万定生冯钧朱跃龙
Owner HOHAI UNIV
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