Remote sensing image picture element and characteristic combination optimizing mixing method
A technology of remote sensing images and fusion methods, applied in image data processing, image data processing, instruments, etc., can solve the problems of distorted spectral characteristics, color distortion, correct identification and classification of unfavorable images, etc., to improve spectral information indicators, high spatial Resolution, the effect of reducing distortion
Inactive Publication Date: 2007-03-07
SHANGHAI JIAOTONG UNIV
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However, this classic IHS fusion method has certain defects. Because the data of different bands have different spectral characteristic curves, the IHS fusion method distorts the original spectral characteristics and produces different degrees of spectral degradation, which is not conducive to image The correct identification and classification, especially for the image fusion of multi-sensor remote sensing images of different time phases, the IHS fusion method cannot make the color tone of the fusion image consistent with the color tone of the original multispectral image, which is caused by the transformation of spectral information. Images cannot be used for object recognition and inversion
Te-Ming et al. conducted a mathematical proof in the IHS space, discussed the defects of the IHS fusion method, and concluded that although it is used to replace the intensity component I 0 High resolution panchromatic image of I new Before the replacement, the statistical characteristics of the image were matched, but the matching error δ=I new -I causes color distortion
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[0024] In order to better understand the technical solutions of the present invention, further descriptions will be made below in conjunction with the embodiments of the accompanying drawings.
[0025] The detailed process flow of the present invention is shown in Figure 1. The present invention selects a multi-spectral remote sensing image B (512×512) as shown in Figure 2(a), and a high-resolution panchromatic remote sensing image A (512×512) as shown in Figure 2(b), after A and B are strictly registered, the implementation Follow the steps below:
[0026] 1. Perform IHS transformation on the multispectral image B to obtain the chroma H, saturation S and intensity component I in the IHS color space respectively, and then perform three-level wavelet decomposition on the I component;
[0027] 2. Perform linear stretching and histogram matching on the high-resolution image A, and then perform wavelet decomposition, and the number of decomposition layers is also 3;
[0028] 3. ...
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The method carries on the optimum mixture in picture element grade with two characteristic indexes of space detail information and spectral information at IHS space by utilizing low-frequency baseband coefficient obtained from wavelet multilayer decomposition of multispectral image intensity component and low-frequency baseband coefficient obtained from corres ponding multilayer wavelet decomposition of high resolution image. The new intensity component is obtained by carrying on characteristic grade mixture of high-frequency coefficient decomposed with wavelet and then carrying on wavelet inverse transform for wavelet coefficient. Finally, the mixed image is obtained after IHS inverse transform is done.
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Technical field: [0001] The present invention relates to a remote sensing image pixel and feature joint optimal fusion method, which combines the time-frequency characteristics of wavelet multi-resolution decomposition and the IHS (Intensity-Chroma Hue-Saturation) transformation fusion method to perform pixel-level and feature fusion. Level joint optimal fusion is the core technology of remote sensing image fusion, and it can be widely used in various military or civilian remote sensing information processing systems, digital city spatial information systems and other fields. Background technique: [0002] How to effectively fuse high-resolution panchromatic remote sensing images and low-resolution multispectral remote sensing images, and balance the two characteristic indicators of spatial detail information and spectral information in the fusion results is one of the research hotspots in multi-source remote sensing image fusion technology. [0003] The IHS fusion method fi...
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IPC IPC(8): G01S7/48G06T1/00
Inventor 敬忠良肖刚周前祥李建勋
Owner SHANGHAI JIAOTONG UNIV