CN112085685B - Space-time fusion method capable of eliminating brick effect and based on space mixing decomposition - Google Patents
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Abstract
The invention relates to a space-time fusion method based on space mixing decomposition, which can eliminate brick effect, and comprises the following steps: firstly, decomposing a low spatial resolution image at a predicted moment based on the existing spatial hybrid decomposition method to obtain an initial fusion image; then, counting mixed decomposition residual errors and space continuity measures of all low-resolution pixels, and determining amplitude parameters; and finally, by using an iterative method, taking the initial fusion image as an initial value, simultaneously minimizing the difference of the reflectivities of the mixed decomposition residual error and the similar ground objects in the neighborhood, and obtaining the optimal reflectivities of various ground objects by implementing dynamic constraint, and reconstructing the fusion image. Compared with the prior art, the method can effectively eliminate the brick effect generated in the existing space mixing decomposition method, and can effectively improve the space-time fusion precision in both precision evaluation and visual display; in addition, the invention can be universally applied to various space-time fusion methods based on space mixing decomposition, and has extremely high application value in the field.
Description
Technical Field
The invention relates to the technical field of remote sensing image fusion, in particular to a space-time fusion method based on space mixing decomposition, which can eliminate brick effects.
Background
Landsat and Terra/Aqua satellites are satellites currently in wide use for global observation. The time and the spatial resolution of the Landsat and MODIS data obtained by the method are mutually restricted due to the limitations of the technical level, the manufacturing cost and the like. The spatial resolution of the Landsat data is 30m, a scene is obtained every 16 days, but the available Landsat data is usually less due to factors such as cloud and fog shielding. The spatial resolution of the MODIS data is 500m, but at least one scene is available daily. The requirement of real-time fine monitoring of the ground is difficult to meet by utilizing Landsat or MODIS data alone. The remote sensing data space-time fusion technology can fuse the two images to obtain the remote sensing image with high time and spatial resolution. Currently commonly used Spatio-temporal fusion methods include methods Based on spatial weighting (e.g., spatio-temporal adaptive reflectivity fusion model (Spatial and Temporal Adaptive Reflectance Fusion Model, STARFM), enhanced Spatio-temporal adaptive reflectivity fusion model (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, ESTARFM)), methods Based on machine learning (e.g., sparse representation), and methods Based on spatial hybrid decomposition (e.g., hybrid decomposition-Based data fusion (un-Based Data Fusion, UBDF), remote sensing data Spatio-temporal fusion methods (Spatial and Temporal Data Fusion Approach, STDFA), virtual data pair-Based spatial hybrid decomposition methods (Virtual Image Pair-Based space-Temporal Fusion with Spatial Unmixing, VIPSTF-SU)), and the like. Among them, the method based on spatial hybrid decomposition is a classical method proposed earlier, and is widely accepted and applied in the field of space-time fusion.
Methods based on spatial hybrid decomposition have many advantages over other methods. The method has low requirement on the known high-spatial resolution information, and has good application value in the area with lack of data. However, the reflectivity of various ground objects obtained in the adjacent low-spatial resolution pixels based on the spatial mixed decomposition method may be different, so that the same ground object presents different gray values in the low-spatial resolution pixels, namely, obvious brick effect exists. The problem greatly affects the prediction accuracy and visual effect of space-time fusion, but is not solved effectively so far.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a space-time fusion method based on spatial mixing decomposition, which can eliminate brick effects.
The aim of the invention can be achieved by the following technical scheme:
a space-time fusion method based on spatial hybrid decomposition capable of eliminating brick effect, comprising the following steps:
s1: and (3) establishing a window for each low-resolution pixel by taking the low-resolution pixel as a center, performing mixed decomposition on the low-resolution image at the predicted moment by using the input high-spatial resolution classification map based on a known spatial mixed decomposition method, acquiring an initial fusion image, and calculating a mixed decomposition residual error of each center pixel.
S2: according to the input high spatial resolution classification diagram, determining pixels which cover the same ground object category as the central pixel in a window taking the low resolution pixel as the center, obtaining an indication function, and calculating the spatial continuity measure of each central pixel according to the initial fusion image.
The indication function I i,j,c The expression of (2) is:
wherein c is the ground object type number.
Spatial continuity measure D of each center pixel i The calculation formula of (2) is as follows:
wherein: i i,j,c For indication function, C is the number of the ground object types, C is the total number of the ground object types, N 0 In the UBDF method, E is the number of low-resolution pixels in a window centering on a certain low-resolution pixel i,c The reflectivity of the c-type ground object of the center pixel, E j,c The reflectivity of the class c ground object of the neighborhood pixel; e in STDFA and VIPSTF-SU methods i,c The reflectivity change quantity of the c-th type ground object of the center pixel E j,c The reflectivity variation of the c-th type ground object of the neighborhood pixel.
S3: and acquiring the statistical information of the mixed decomposition residual error of each center pixel and the statistical information of the spatial continuity measure, and calculating the amplitude parameter according to the two statistical information. The calculation expression of the amplitude parameter A is as follows:
wherein: r is R M For mode of mixed decomposition residual R, D M Is the mode of the spatial continuity measure D.
S4: and constructing an objective function for the center pixel according to the reflectivity value and the spatial continuity assumption of the low-resolution image at the predicted moment.
The expression of the objective function is:
wherein: alpha is a set balance parameter, R i For each center pixel, a is the calculated amplitude parameter, D i For the space continuity measure of each center pixel, P is the ratio matrix of various ground objects in the window with the low-resolution pixel as the center, t is the iteration times, C is the total number of ground object categories, C is the ground object type number, N 0 I is the number of low resolution picture elements in a window centered on the low resolution picture element i,j,c Is an indication function; in the process of the UBDF,
each type of ground object reflectivity vector of each center pixel to be solved for the iteration; q is a vector formed by the reflectivities of all pixels in a window taking the low-resolution pixel as the center; in the STDFA method, the ∈>
Each center pixel has various ground object reflectivity change vectors at two moments of the solution required by the iteration; q is the reflectance change vector between two moments of each pixel in the window taking the low resolution pixel as the center; in the VIPSTF-SU method, +.>
Each center pixel is provided with various ground object reflectivity change vectors for the predicted time and the virtual time which are needed to be solved in the iteration; q is a corresponding reflectance change vector in a window centered on the low resolution pixel; in UBDF method, the->
C-th type of ground for each center pixel to be solved for the iterationReflectivity of (I)>
The c-th type ground object reflectivity of the neighborhood pixel which is obtained in the last iteration is obtained; in the STDFA and VIPSTF-SU methods, < > and->
For the c-th type ground object reflectivity variation of each center pixel needed to be solved in the iteration, the weight of the c-th type ground object is +.>
And obtaining the c-th type ground object reflectivity variation of the neighborhood pixel for the last iteration.
S5: and (3) traversing all the low-resolution pixels, taking the initial fusion image obtained in the step (S1) as an iteration initial value, inputting the initial fusion image and the calculated amplitude parameter into an objective function, and obtaining the optimal reflectivity of various ground objects of the center pixel through iteration until the objective function value is minimum.
S6: reconstructing a final fusion image according to the spatial resolution classification diagram and the acquired optimal reflectivity of various ground features.
Compared with the prior art, the space-time fusion method based on space mixing decomposition, which can eliminate the brick effect, has the following beneficial effects:
1. the eliminating effect on the brick effect is obvious, and the precision and visual display of the fusion image are obviously improved: the method expands the classical spatial mixed decomposition method, innovatively adds the spatial continuity measure in the objective function, balances the influence of data fidelity and spatial continuity through parameters, and fully excavates the spatial structure information between adjacent pixels with low spatial resolution;
2. the method has good universality: the method of the invention follows the basic assumption of the classical spatial mixed decomposition method, expands the objective function at the same time, can be applied to any spatial mixed decomposition method at present, and has high application value for new spatial mixed decomposition methods possibly proposed in the future;
3. the method of the invention can also be coupled with other improved spatial mixing decomposition methods to obtain higher-precision results: the method of the invention does not change the basic assumption of the classical spatial mixed decomposition method and can be integrated with other constraint terms.
Drawings
FIG. 1 is a flow chart of a space-time fusion method based on spatial hybrid decomposition that can eliminate brick effects in an embodiment;
fig. 2 is a graph showing the results of heterogeneous regions in a simulation experiment, wherein (a) is an image fusion result using an original UBDF-based spatial hybrid decomposition method, (b) is an image fusion result using an UBDF-BR of the present invention, (c) is an image fusion result using an original STDFA-BR, and (d) is an image fusion result using an STDFA-BR of the present invention, (e) is an image fusion result using an original VIPSTF-SU-based spatial hybrid decomposition method, and (f) is an image fusion result using a VIPSTF-SU-BR of the present invention, and (g) is a reference image.
Fig. 3 is a graph showing the results of the change region in the simulation experiment of the embodiment, wherein (a) is the result of image fusion using the original UBDF-based spatial hybrid decomposition method, (b) is the result of image fusion using the UBDF-BR of the present invention, (c) is the result of image fusion using the original STDFA-BR of the present invention, (d) is the result of image fusion using the STDFA-BR of the present invention, (e) is the result of image fusion using the original VIPSTF-SU-based spatial hybrid decomposition method, (f) is the result of image fusion using the VIPSTF-SU-BR of the present invention, and (g) is the reference image.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
Examples
As shown in fig. 1, the present invention relates to a space-time Fusion method (SU-BR) Based on spatial hybrid decomposition, which can eliminate brick effects, and is used for eliminating brick effects in a fused image obtained by using an original space-time Fusion method Based on spatial hybrid decomposition, and specifically comprises the following steps:
wherein P represents the duty ratio matrix of various ground objects in the window taking the low-resolution pixel as the center; in the UBDF method, E i Representing various ground object reflectivity vectors of each center pixel to be solved; q represents a vector formed by the reflectivities of all pixels in a window taking the low-resolution pixel as a center; in the STDFA method, E i Representing various ground object reflectivity change vectors of each center pixel at two moments; q represents the reflectance change vector between two times of each pixel in the window taking the low resolution pixel as the center; in the VIPSTF-SU method, E i Representing various ground object reflectivity change vectors of each center pixel between the predicted time and the virtual time; q represents the corresponding reflectance change vector in the window centered on the low resolution picture element.
Step 2, according to the classification diagram, determining the pixels covering the same ground object category as the central low resolution pixel in the window with the low resolution pixel as the center to obtain an indication function I i,j,c . Calculating the spatial continuity measure D of each center low-resolution pixel according to the initial fusion image obtained in the step 1 i 。I i,j,c And D i Definition of (2)The following are provided:
wherein C is the total number of the ground object categories; n (N) 0 The number of the low-resolution pixels in the window taking the low-resolution pixel as the center; in the UBDF method, E i,c The reflectivity of the c-th type ground object of the center pixel; e (E) j,c The reflectivity of the class c ground object of the neighborhood pixel; e in STDFA and VIPSTF-SU methods i,c The reflectivity variation of the c-th type ground object of the center pixel; e (E) j,c The reflectivity variation of the c-th type ground object of the neighborhood pixel.
Step 3, calculating amplitude parameters according to the mixed decomposition residual obtained in the step 1 and the statistical information (such as mode) of the spatial continuity measure obtained in the step 2
Wherein R is M For mode of mixed decomposition residual R, D M Is the mode of the spatial continuity measure D.
And 4, constructing the following objective function for the window center low-resolution pixel according to the reflectivity value and the spatial continuity assumption of the low-resolution image at the predicted moment:
wherein t is the iteration number,
for the amount of solution needed for this iteration, in UBDF method,/>
At the t-th iteration, middleC-type ground object reflectivity of the heart pixel; in the STDFA and VIPSTF-SU methods, < > and->
When the iteration is the t time, the reflectivity variation of the c-th type ground object of the center pixel; />
For the quantities that have been found in the last iteration, α is a set trade-off parameter, whose value is a number between 0 and 1.
The step also needs to set a threshold value or iteration times for providing a judgment basis for the next iteration termination condition.
And 5, sequentially accessing all the low-resolution pixels, taking the initial fusion image obtained in the step 1 as an iteration initial value, inputting the obtained amplitude parameter A and the set balance parameter alpha, and substituting the obtained amplitude parameter A and the set balance parameter alpha into an objective function for iteration. Gradually minimizing the objective function value through iteration, thereby obtaining the optimal reflectivity of various ground objects of the window center low resolution pixel
The set iteration termination condition is 1) the preset iteration times are reached; or 2) E i The amount of change is less than the set threshold three times in succession. Specifically:
and (3) taking the initial fusion image obtained in the step (1) as an iteration initial value, inputting the obtained amplitude parameter A and the set balance parameter alpha, and substituting the obtained amplitude parameter A and the set balance parameter alpha into an objective function. Judging whether all the low-resolution pixels are accessed, if so, judging whether the current iteration can be terminated, otherwise, continuing to access the low-resolution pixels until the iteration termination condition is reached. If the iteration termination condition is reached, obtaining the optimal reflectivity of various ground objects of the low-resolution pixel in the center of the window by gradually minimizing the objective function value
Then executing the next step, otherwise, executing the next iteration, and then executing all the pixel access steps again.
And 6, reconstructing a final fusion image according to the classification map and the optimal reflectivity of various ground objects.
In order to verify the effectiveness of the method of the present invention, the present embodiment predicts fusion images using the method of the present invention. The space-time fusion method (spatial mixing-based spatial-temporal fusion) based on spatial mixing decomposition comprises three common classical methods UBDF, STDFA, VIPSTF-SU, and the method of the invention is respectively applied to the three methods. The following abbreviations refer to the meanings: UBDF-BR: UBDF method capable of eliminating brick effect; STDFA-BR: STDFA method capable of eliminating brick effect; VIPSTF-SU-BR: the VIPSTF-SU method can eliminate brick effect. This example compares the predicted results with existing classical spatial hybrid decomposition methods (UBDF, STDFA and VIPSTF-SU). The two test areas are located in the south of new south wilfordii in australia (heterogeneous area) and in the north of new south wilfory in australia (change area), respectively. As shown in fig. 2 and 3, the fused image results of the two regions are respectively that the upper graph of each sub-graph is the overall fused image graph, and the lower graph of each sub-graph is the enlarged sub-region image graph.
As can be seen from fig. 2 and 3, the UBDF results have obvious brick effects and serious spectral distortions, and the STDFA and VIPSTF-SU methods have better prediction result accuracy due to the spatial mixing decomposition of the changed images and the addition of high spatial resolution multispectral information at known moments, but still have brick effects. Because in the method of the invention, the spatial structure information is fully mined by means of the spatial continuity measure, the spatial continuity and the data fidelity in the window are incorporated into the objective function, and the iteration mode of dynamic constraint is adopted, the brick effect is eliminated, and the spectrum information of the original low-resolution data is well maintained. Thus, the results of the present invention are greatly improved in visual display.
The fused images obtained by each method were evaluated for accuracy using root mean square error (Root Mean Square Error, RMSE) and correlation coefficient (Correlation Coefficient, CC) evaluation index, as shown in table 1. Wherein the RMSE measures the difference between the predicted image and the reference image, the larger the value of which indicates that the predicted image deviates from the reference image; CC reflects the correlation between the predicted image and the reference image, and a larger value indicates that the predicted image and the reference image are closer.
TABLE 1 evaluation of precision of image fusion results
As can be seen from the objective evaluation results in Table 1, the accuracy of the method is obviously improved, and various indexes indicate that the method can obtain the fusion image which is closer to the real situation. In summary, the spatial mixing decomposition method for eliminating the brick effect has obvious advantages from the visual and precision evaluation point of view, and the obtained fusion image can better keep the spectrum and spatial information of the ground object, so that the method is a feasible and effective space-time fusion method.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions may be made without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (5)
1. A space-time fusion method based on spatial mixing decomposition capable of eliminating brick effect, which is characterized by comprising the following steps:
1) Establishing a window for each low-resolution pixel by taking the low-resolution pixel as a center, performing mixed decomposition on the low-resolution image at the predicted moment by using an input high-spatial resolution classification image based on a known spatial mixed decomposition method, acquiring an initial fusion image, and calculating a mixed decomposition residual error of each center pixel;
2) According to the input high spatial resolution classification diagram, determining pixels which cover the same ground object category as the central pixel in a window taking the low resolution pixel as the center, obtaining an indication function, and calculating the spatial continuity measure of each central pixel according to the initial fusion image;
3) Acquiring statistical information of mixed decomposition residual errors of each center pixel and statistical information of space continuity measurement, and calculating amplitude parameters according to the two statistical information;
4) Constructing an objective function for the center pixel according to the reflectivity value and the spatial continuity assumption of the low-resolution image at the predicted moment;
5) Traversing all the low-resolution pixels, taking the initial fusion image obtained in the step 1) as an iteration initial value, inputting the initial fusion image and the calculated amplitude parameter into an objective function, and obtaining the optimal reflectivity of various ground objects of the center pixel through iteration until the objective function value is minimum;
6) Reconstructing a final fusion image according to the spatial resolution classification diagram and the acquired optimal reflectivity of various ground features.
2. The spatial-hybrid decomposition-based spatio-temporal fusion method of eliminating the effect of bricks according to claim 1, characterized in that in step 2) said indication function I i,j,c The expression of (2) is:
wherein c is the ground object type number.
3. The spatial-hybrid decomposition-based spatio-temporal fusion method of eliminating the effect of bricks according to claim 1, wherein in step 2), the spatial continuity measure D of each central pixel i The calculation formula of (2) is as follows:
wherein: i i,j,c For indication function, C is the number of the ground object types, C is the total number of the ground object types, N 0 In the UBDF method, E is the number of low-resolution pixels in a window centering on a certain low-resolution pixel i,c The reflectivity of the c-type ground object of the center pixel, E j,c The reflectivity of the class c ground object of the neighborhood pixel; e in STDFA and VIPSTF-SU methods i,c The reflectivity change quantity of the c-th type ground object of the center pixel E j,c The reflectivity variation of the c-th type ground object of the neighborhood pixel.
4. The spatial-hybrid decomposition-based spatio-temporal fusion method of eliminating brick effects according to claim 1, wherein in step 4), said objective function is expressed as:
wherein: alpha is a set balance parameter, R i For each center pixel, a is the calculated amplitude parameter, D i For the space continuity measure of each center pixel, P is the ratio matrix of various ground objects in the window with the low-resolution pixel as the center, t is the iteration times, C is the total number of ground object categories, C is the ground object type number, N 0 I is the number of low resolution picture elements in a window centered on the low resolution picture element i,j,c Is an indication function; in the process of the UBDF,
each type of ground object reflectivity vector of each center pixel to be solved for the iteration; q is a vector formed by the reflectivities of all pixels in a window taking the low-resolution pixel as the center; in the STDFA method, the ∈>
Each central pixel between two moments of the solution required for the current iterationVarious ground object reflectivity change vectors; q is the reflectance change vector between two moments of each pixel in the window taking the low resolution pixel as the center; in the VIPSTF-SU method, +.>
Each center pixel is provided with various ground object reflectivity change vectors for the predicted time and the virtual time which are needed to be solved in the iteration; q is a corresponding reflectance change vector in a window centered on the low resolution pixel; in UBDF method, the->
C-th type ground object reflectivity of each center pixel to be solved for the iteration>
The c-th type ground object reflectivity of the neighborhood pixel which is obtained in the last iteration is obtained; in the STDFA and VIPSTF-SU methods, < > and->
For the c-th type ground object reflectivity variation of each center pixel needed to be solved in the iteration, the weight of the c-th type ground object is +.>
And obtaining the c-th type ground object reflectivity variation of the neighborhood pixel for the last iteration.
5. The spatial-hybrid decomposition-based spatio-temporal fusion method of eliminating the effect of bricks according to claim 1, wherein in step 3), the calculation expression of the amplitude parameter a is:
wherein: r is R M For mode of mixed decomposition residual R, D M Mode as spatial continuity measure D。
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