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bicubic interpolation method matlab r2012a  (MathWorks Inc)


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    MathWorks Inc bicubic interpolation method matlab r2012a
    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) <t>bicubic</t> <t>interpolation;</t> ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.
    Bicubic Interpolation Method Matlab R2012a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/bicubic interpolation method matlab r2012a/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    bicubic interpolation method matlab r2012a - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization"

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    Journal: Sensors (Basel, Switzerland)

    doi: 10.3390/s150102041

    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.
    Figure Legend Snippet: Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Techniques Used:

    Comparison Results of A-PSNR, A-SSIM and SAM of the Different Methods.
    Figure Legend Snippet: Comparison Results of A-PSNR, A-SSIM and SAM of the Different Methods.

    Techniques Used: Comparison

    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of the original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.
    Figure Legend Snippet: Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of the original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Techniques Used:

    Comparison results of A-PSNR, A-SSIM and SAM of the different methods.
    Figure Legend Snippet: Comparison results of A-PSNR, A-SSIM and SAM of the different methods.

    Techniques Used: Comparison

    Experimental results of Letter paper HSI dataset (color composite of R: 31, G: 20, B: 8). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.
    Figure Legend Snippet: Experimental results of Letter paper HSI dataset (color composite of R: 31, G: 20, B: 8). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Techniques Used:

    The cropped portions of the (color composite of R: 31, G: 20, B: 8). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.
    Figure Legend Snippet: The cropped portions of the (color composite of R: 31, G: 20, B: 8). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Techniques Used:

    Experimental results of FS-NUST HSI dataset (color composite of R: 52, G: 32, B: 13). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.
    Figure Legend Snippet: Experimental results of FS-NUST HSI dataset (color composite of R: 52, G: 32, B: 13). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Techniques Used:

    The cropped portions of the (color composite of R: 52, G: 32, B: 13). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.
    Figure Legend Snippet: The cropped portions of the (color composite of R: 52, G: 32, B: 13). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Techniques Used:



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    bicubic interpolation method matlab r2012a  (MathWorks Inc)
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    MathWorks Inc bicubic interpolation method matlab r2012a
    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) <t>bicubic</t> <t>interpolation;</t> ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.
    Bicubic Interpolation Method Matlab R2012a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/bicubic interpolation method matlab r2012a/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    bicubic interpolation method matlab r2012a - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques:

    Comparison Results of A-PSNR, A-SSIM and SAM of the Different Methods.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Comparison Results of A-PSNR, A-SSIM and SAM of the Different Methods.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques: Comparison

    Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of the original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Experimental results of PaviaU HSI (color composite of R: 80, G: 28, B: 9). ( a ) the false color image of the original HSI; ( b ) bicubic interpolation; ( c ) PCA fusion method; ( d ) WT fusion method; ( e ) P + XS fusion method; ( f ) SR-SR method; ( g ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques:

    Comparison results of A-PSNR, A-SSIM and SAM of the different methods.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Comparison results of A-PSNR, A-SSIM and SAM of the different methods.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques: Comparison

    Experimental results of Letter paper HSI dataset (color composite of R: 31, G: 20, B: 8). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Experimental results of Letter paper HSI dataset (color composite of R: 31, G: 20, B: 8). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques:

    The cropped portions of the (color composite of R: 31, G: 20, B: 8). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: The cropped portions of the (color composite of R: 31, G: 20, B: 8). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques:

    Experimental results of FS-NUST HSI dataset (color composite of R: 52, G: 32, B: 13). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: Experimental results of FS-NUST HSI dataset (color composite of R: 52, G: 32, B: 13). ( a ) original LR HSI; ( b ) bicubic interpolation method; ( c ) SR-SR method; ( d ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques:

    The cropped portions of the (color composite of R: 52, G: 32, B: 13). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Hyperspectral Imagery Super-Resolution by Compressive Sensing Inspired Dictionary Learning and Spatial-Spectral Regularization

    doi: 10.3390/s150102041

    Figure Lengend Snippet: The cropped portions of the (color composite of R: 52, G: 32, B: 13). ( a ) bicubic interpolation method; ( b ) SR-SR method; ( c ) the proposed method.

    Article Snippet: The results are compared with the reconstructed images obtained by bicubic interpolation method (implemented with MATLAB R2012a), principal component analysis (PCA) image fusion method [ ], a discrete wavelet transform (WT) image fusion method [ ] and a variational model for P + XS image fusion [ ] (the software and documentation is available online at: www.math.ucla.edu/∼wittman/pansharpening ), and sparse representation-based SR (SR-SR) method [ ].

    Techniques: