Fusion of hyperspectral and panchromatic images with guided filter

Guided filter has been widely used in image fusion. However, most of the guided filter-based fusion methods generate the spatial detail image by making a compromise between the spatial detail of the panchromatic (PAN) and that of the hyperspectral (HS) intensity component. The intensity component cannot well present the edge and texture features of the HS image. The spectral distortion usually occurs due to the injected redundant spatial detail. To overcome this problem, this study presents a novel HS image fusion method by taking the advantage of the guided filter. The characteristics of the PAN and HS images are simultaneously considered. The guided filter is employed to generate the spatial detail image of each HS image band successively. The generated spatial detail image is further optimized by minimizing the difference between each band of the spatial detail image and its corresponding band of the HS image, with the help of a novel injection gains matrix. Experiments performed on various satellite datasets demonstrate that the superiority of the proposed method in spectral maintenance and spatial quality aspects.

[1]  Abdul Ghafoor,et al.  Guided Filter and IHS-Based Pan-Sharpening , 2016, IEEE Sensors Journal.

[2]  Bruno Aiazzi,et al.  Improving Component Substitution Pansharpening Through Multivariate Regression of MS $+$Pan Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Jocelyn Chanussot,et al.  Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction , 2012, EURASIP J. Adv. Signal Process..

[4]  Jocelyn Chanussot,et al.  Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Aleksandra Pizurica,et al.  Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  P. Chavez,et al.  Extracting spectral contrast in landsat thematic mapper image data using selective principal component analysis , 1989 .

[7]  Naoto Yokoya,et al.  Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Jean-Yves Tourneret,et al.  Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Kishor P. Upla,et al.  Multiresolution image fusion using edge-preserving filters , 2015 .

[10]  Te-Ming Tu,et al.  A new look at IHS-like image fusion methods , 2001, Inf. Fusion.

[11]  Jocelyn Chanussot,et al.  Contrast and Error-Based Fusion Schemes for Multispectral Image Pansharpening , 2014, IEEE Geoscience and Remote Sensing Letters.

[12]  Mohit Sharma,et al.  Image fusion based on image decomposition using self-fractional Fourier functions , 2014, Signal Image Video Process..

[13]  Liangpei Zhang,et al.  On Combining Multiple Features for Hyperspectral Remote Sensing Image Classification , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Jocelyn Chanussot,et al.  A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[15]  A. Mookambiga,et al.  Comprehensive review on fusion techniques for spatial information enhancement in hyperspectral imagery , 2016, Multidimens. Syst. Signal Process..

[16]  Jian Sun,et al.  Guided Image Filtering , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  J. G. Liu,et al.  Smoothing Filter-based Intensity Modulation: A spectral preserve image fusion technique for improving spatial details , 2000 .

[18]  Hassan Ghassemian,et al.  A review of remote sensing image fusion methods , 2016, Inf. Fusion.

[19]  Jocelyn Chanussot,et al.  Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Xiaorun Li,et al.  Blind nonlinear hyperspectral unmixing based on constrained kernel nonnegative matrix factorization , 2012, Signal, Image and Video Processing.

[21]  L. Wald,et al.  Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images , 1997 .

[22]  Luciano Alparone,et al.  MTF-tailored Multiscale Fusion of High-resolution MS and Pan Imagery , 2006 .

[23]  Jae Wook Jeon,et al.  Efficient image sharpening and denoising using adaptive guided image filtering , 2015, IET Image Process..

[24]  Jean-Yves Tourneret,et al.  Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation , 2015, IEEE Transactions on Image Processing.

[25]  B. K. Shreyamsha Kumar,et al.  Image fusion based on pixel significance using cross bilateral filter , 2013, Signal, Image and Video Processing.