Fusion of panchromatic image with multi-spectral image using robust adaptive normalized convolution

2019 ◽  
Vol 169 ◽  
pp. 118-124
Author(s):  
K. Joseph Abraham Sundar
Keyword(s):  
Spectral Image ◽  
Panchromatic Image ◽  
Robust Adaptive ◽  
Normalized Convolution

Multi-Spectral Image Fusion Using Intensity Modulation and Non-Separable Wavelet Frame

2005 ◽  
Author(s):  
Xuhong Yang ◽  
Zhongliang Jing ◽  
Jian-Xun Li
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Spatial Resolution ◽  
Intensity Modulation ◽  
Spectral Information ◽  
Wavelet Frame ◽  
Remote Sensing Images ◽  
Spectral Image ◽  
Panchromatic Image ◽  
Fusion Approach

A fusion approach is proposed to refine the resolution of multi-spectral images using the corresponding high-resolution panchromatic images. The technique is based on intensity modulation and non-separable wavelet frame. The high-resolution panchromatic image is decomposed by the non-separable wavelet frame. Then the wavelet coefficients are used as the factor of modulating to modulate the multi-spectral image. Experimental results indicate that, comparing with the traditional methods, the proposed method can efficiently preserve the spectral information while improving the spatial resolution of remote sensing images.

scholarly journals NEW HYBRID PAN-SHARPENING METHOD BASED ON TYPE-1 FUZZY-DWT STRATEGY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 247-254
Author(s):  
F. Dadras Javan ◽  
F. S. Mortazavi ◽  
F. Moradi ◽  
A. Toosi
Keyword(s):  
Hybrid Algorithm ◽  
High Spatial Resolution ◽  
Computational Cost ◽  
The Other ◽  
Spectral Image ◽  
Panchromatic Image ◽  
Spatial Quality ◽  
Assessment Metrics ◽  
Wavelet Algorithm

Abstract. The purpose of image fusion is to combine two images from the same view in order to produce an image with more information and higher quality. In this paper, a panchromatic image with high spatial resolution and a low-resolution multi-spectral image having rich spectral information are fused together to produce a high-resolution multi-spectral image that heritage the characteristics of both initial images. For this purpose, a hybrid pan-sharpening method, called ‘Improved Fuzzy-DWT’ have been proposed based on the modification of the parameters existed in the latest version of Fuzzy-Wavelet algorithm, and then it was compared with some other algorithms such as PCA, Gram-Schmidt, Wavelet, and two of its hybrid derivatives called PCA-Wavelet and IHS-wavelet. The comparison was conducted using DIV, SSIM, SID, CC, DS, and QNR spectral and spatial quality assessment metrics. The obtained results demonstrate that the proposed hybrid algorithm has relatively better performance in comparison with the other mentioned pan-sharpening techniques in terms of both spectral and spatial qualities, regarding it was superior in terms of SID, DIV, SSIM, DS. From the computational cost standpoint, the proposed method has the most running time compared with the other methods.

scholarly journals Pansharpening based on convolutional autoencoder and multi-scale guided filter

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Ahmad AL Smadi ◽  
Shuyuan Yang ◽  
Zhang Kai ◽  
Atif Mehmood ◽  
Min Wang ◽  
...  
Keyword(s):  
Spectral Characteristics ◽  
Remote Sensing Data ◽  
Image Features ◽  
Guided Filter ◽  
Spectral Image ◽  
Multi Scale ◽  
Panchromatic Image ◽  
Image Patches ◽  
Convolutional Autoencoder ◽  
Scale Down

AbstractIn this paper, we propose a pansharpening method based on a convolutional autoencoder. The convolutional autoencoder is a sort of convolutional neural network (CNN) and objective to scale down the input dimension and typify image features with high exactness. First, the autoencoder network is trained to reduce the difference between the degraded panchromatic image patches and reconstruction output original panchromatic image patches. The intensity component, which is developed by adaptive intensity-hue-saturation (AIHS), is then delivered into the trained convolutional autoencoder network to generate an enhanced intensity component of the multi-spectral image. The pansharpening is accomplished by improving the panchromatic image from the enhanced intensity component using a multi-scale guided filter; then, the semantic detail is injected into the upsampled multi-spectral image. Real and degraded datasets are utilized for the experiments, which exhibit that the proposed technique has the ability to preserve the high spatial details and high spectral characteristics simultaneously. Furthermore, experimental results demonstrated that the proposed study performs state-of-the-art results in terms of subjective and objective assessments on remote sensing data.

An Improved Image Fusion Algorithm Based on IHS and Wavelet Transform

2013 ◽  
Vol 427-429 ◽  
pp. 1641-1644
Author(s):  
Liu Ming ◽  
Shu Hui Li
Keyword(s):  
Wavelet Transform ◽  
High Resolution ◽  
Image Fusion ◽  
Wavelet Transformation ◽  
Experiment Research ◽  
Fusion Image ◽  
Fusion Algorithm ◽  
Spectral Image ◽  
Panchromatic Image ◽  
Ihs Transform

A new improved image fusion algorithm is proposed for multi-spectral image (MUL) and the high-resolution panchromatic image (PAN) based on intensity-hue-saturation (IHS) transform combined with wavelet transformation (WT). Firstly, the multi-spectral image is transformed into the IHS space for getting the intensity component (I).Then the high-resolution panchromatic image and I were matched with histogram. Secondly, the PAN and I were decomposed respectively by WT and fused to obtain the new I by the inverse WT. Finally, the fusion image was obtained by inverse IHS transform. four evaluate indicators are defined in this paper. By experiment research, the results show that this new method can effectively improve the fusion effect.

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