An edge preserving multi-resolution image fusion: Use of joint bilateral filter

Super-resolution (SR) algorithms address the inabilities of poor imaging devices, there by producing high quality images with enhanced resolution. We propose a new SR approach which produces sharp high resolution (HR) image using its low resolution (LR) counterparts. The proposed method uses geometric duality for spatially adapting covariance-based interpolation (CBI). To preserve edge information, a multi-stage cascaded joint bilateral filter (MSCJBF) is proposed as an intermediary stage. These edges are incorporated in the high frequency subbands obtained by the stationary wavelet transform (SWT), through nearest neighbor interpolation (NNI) method. Prior to the NNI process, the high frequency subbands undergo two-lobed lanczos interpolation to achieve the desired resolution enhancement. The quantitative and qualitative analysis for various test images prove the superiority of our method.

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Multimodal medical image fusion based on joint bilateral filter and local gradient energy

Information Sciences ◽

10.1016/j.ins.2021.04.052 ◽

2021 ◽

Author(s):

Xiaosong Li ◽

Fuqiang Zhou ◽

Haishu Tan ◽

Wanning Zhang ◽

Congyang Zhao

Keyword(s):

Image Fusion ◽

Medical Image ◽

Bilateral Filter ◽

Medical Image Fusion ◽

Gradient Energy ◽

Local Gradient ◽

Joint Bilateral Filter

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Cross Bilateral Filter Based Image Fusion in Transform Domain

SSRN Electronic Journal ◽

10.2139/ssrn.3545083 ◽

2020 ◽

Author(s):

Kapil Joshi ◽

N.K. Joshi ◽

Manoj Diwakar ◽

Himanshu Gupta ◽

Dev Baloni

Keyword(s):

Image Fusion ◽

Bilateral Filter ◽

Transform Domain ◽

Cross Bilateral Filter

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Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096511666180607101743 ◽

2019 ◽

Vol 12 (3) ◽

pp. 263-269

Author(s):

Liu Xian-Hong ◽

Chen Zhi-Bin

Keyword(s):

Image Fusion ◽

Sparse Representation ◽

Filter Bank ◽

Guided Filter ◽

Fusion Method ◽

Edge Preserving ◽

Directional Information ◽

Multi Scale ◽

Directional Filter ◽

Image Fusion Method

Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

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Hyperspectral Image Classification Based on Kernel-Guided Deformable Convolution and Double-Window Joint Bilateral Filter

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2021.3084203 ◽

2021 ◽

pp. 1-5

Author(s):

Chunhui Zhao ◽

Wenxiang Zhu ◽

Shou Feng

Keyword(s):

Image Classification ◽

Hyperspectral Image ◽

Bilateral Filter ◽

Hyperspectral Image Classification ◽

Joint Bilateral Filter

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Image Fusion Using Different Edge-preserving Filters

Multi-resolution Image Fusion in Remote Sensing ◽

10.1017/9781108566285.004 ◽

2019 ◽

pp. 52-79

Keyword(s):

Image Fusion ◽

Edge Preserving

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Multimodal Medical Image Fusion using Guided Filter in NSCT Domain

Biomedical & Pharmacology Journal ◽

10.13005/bpj/1566 ◽

2018 ◽

Vol 11 (4) ◽

pp. 1937-1946

Author(s):

Nancy Mehta ◽

Sumit Budhiraja

Keyword(s):

Image Fusion ◽

Medical Image ◽

Similarity Index ◽

Low Frequency ◽

Structural Similarity ◽

Relevant Information ◽

Phase Congruency ◽

Edge Preserving ◽

Medical Image Fusion ◽

Fused Image

Multimodal medical image fusion aims at minimizing the redundancy and collecting the relevant information using the input images acquired from different medical sensors. The main goal is to produce a single fused image having more information and has higher efficiency for medical applications. In this paper modified fusion method has been proposed in which NSCT decomposition is used to decompose the wavelet coefficients obtained after wavelet decomposition. NSCT being multidirectional,shift invariant transform provide better results.Guided filter has been used for the fusion of high frequency coefficients on account of its edge preserving property. Phase congruency is used for the fusion of low frequency coefficients due to its insensitivity to illumination contrast hence making it suitable for medical images. The simulated results show that the proposed technique shows better performance in terms of entropy, structural similarity index, Piella metric. The fusion response of the proposed technique is also compared with other fusion approaches; proving the effectiveness of the obtained fusion results.

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