Non-negative sparse matrix-based WorldView-2 remote sensing panchromatic and multi-spectral image fusion method

A multi-spectral image, non-negative sparse technology, applied in the field of remote sensing panchromatic and multi-spectral image fusion, can solve the problem that the brightness component is not accurate enough, can not solve the problem of detail integration and spectral distortion, and achieve a reasonable extraction algorithm and improved Extraction accuracy, overall high quality results

Active Publication Date: 2016-12-07
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0004] The existing fusion methods are aimed at traditional satellite remote sensing multispectral images. For ultra-high resolution remote sensing images, it is not the optimal image fusion me

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  • Non-negative sparse matrix-based WorldView-2 remote sensing panchromatic and multi-spectral image fusion method
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  • Non-negative sparse matrix-based WorldView-2 remote sensing panchromatic and multi-spectral image fusion method

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Embodiment Construction

[0039] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0040] Step 1. Extract the I component using the non-negative matrix factorization (NMF) method

[0041] As a relatively mature data analysis method, non-negative matrix factorization has been widely used in image analysis, text clustering, data mining, speech processing, etc. Considering that the I component extracted from the multispectral image should be consistent with the spectral response of the panchromatic image as much as possible, the matrix V to be decomposed is composed of the panchromatic image and the eight-band multispectral image in the method of extracting the I component by NMF .

[0042] First, the panchromatic image Pan and the eight-band multispectral image X 1 ,X 2 ,...,X 8 Straighten by row to get P,M 1 , M 2 ,...,M 8 vector, and then compose the matrix V to be decomposed according to the formula (1), namely

[0043] V=[P,...

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Abstract

The invention provides a non-negative sparse matrix-based WorldView-2 (WV-2) remote sensing panchromatic and multi-spectral image fusion method, and relates to the field of image fusion. Multi-spectral images are subjected to brightness component extraction by using a non-negative matrix factorization (NMF) algorithm; and then the images are fused by using hyperspherical color space resolution merge (HCS) transformation to obtain a fused image. The fused image is improved in the aspects of detail injection and spectral preservation to a certain extent, and finally a high-quality fused result is obtained. An NMF method is adopted for I component extraction, so that the brightness component extraction precision is improved. Compared with a comparison algorithm, the method is more reasonable, so that the overall quality of the fused image of a WV-2 satellite is relatively high, the fused image is improved in the aspects of the detail injection and the spectral preservation to a certain extent, subjective evaluation and objective analysis results can reach consistency, the obtained fused image is better in visuality, and a picture is clearer. Compared with a traditional remote sensing panchromatic and multi-spectral image fusion method, the method provided by the invention is more advantageous.

Description

technical field [0001] The invention relates to the field of image fusion, in particular to a method for remote sensing panchromatic and multispectral image fusion. Background technique [0002] In recent years, the number of bands of new satellite remote sensing multispectral images has been increasing, and the resolution of images has also been rapidly improved. Take the WorldView-2 (WV-2) satellite as an example. The WV-2 satellite was launched in 2009 and can provide multi-spectral images with a resolution of 1.84 meters in 8 bands and panchromatic images with a resolution of 0.46 meters in a single band. Compared with traditional satellite images, it has the following characteristics: the number of bands increases, and the spectral division is finer; the spectral coverage of panchromatic images is narrowed, so that the spectral matching with multi-spectral bands has a large change. In remote sensing applications, images with both high spatial and high spectral resoluti...

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Application Information

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IPC IPC(8): G06T5/50
CPCG06T5/50
Inventor 何贵青董丹丹邢思远梁凡夏召强冯晓毅李会方谢红梅吴俊蒋晓悦
Owner NORTHWESTERN POLYTECHNICAL UNIV
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