Cross Bilateral Filter Based Image Fusion in Transform Domain

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

Multi-modality medical image fusion using cross-bilateral filter and neuro-fuzzy approach

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Harmeet Kaur ◽  
Satish Kumar ◽  
KuljinderSingh Behgal ◽  
Yagiyadeep Sharma
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Bilateral Filter ◽  
Fuzzy Approach ◽  
Medical Image Fusion ◽  
Neuro Fuzzy ◽  
Cross Bilateral Filter

Magnetic resonance and computed tomography image fusion using saliency map and cross bilateral filter

2019 ◽  
Vol 13 (6) ◽  
pp. 1157-1164 ◽  
Author(s):  
M. Munawwar Iqbal Ch ◽  
M. Mohsin Riaz ◽  
Naima Iltaf ◽  
Abdul Ghafoor ◽  
Muhammad Attique Sadiq
Keyword(s):  
Computed Tomography ◽  
Magnetic Resonance ◽  
Image Fusion ◽  
Bilateral Filter ◽  
Saliency Map ◽  
Tomography Image ◽  
Cross Bilateral Filter ◽  
Computed Tomography Image

Medical Image Fusion Based on SWT and Cross Bilateral Filter

2021 ◽  
pp. 893-899
Author(s):  
Shaik Gowhar ◽  
Maruturi Haribabu ◽  
Velmathi Guruviah
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Bilateral Filter ◽  
Medical Image Fusion ◽  
Cross Bilateral Filter

scholarly journals Image Fusion based on Cross Bilateral and Rolling Guidance Filter through Weight Normalization

2020 ◽  
Vol 13 (1) ◽  
pp. 51-61
Author(s):  
Dawa C. Lepcha ◽  
Bhawna Goyal ◽  
Ayush Dogra
Keyword(s):  
Image Fusion ◽  
Vision System ◽  
Bilateral Filter ◽  
Small Scale ◽  
Fused Image ◽  
Current Scenario ◽  
Scale Structures ◽  
Cross Bilateral Filter ◽  
Military Units ◽  
Small Scale Structures

Introduction: Image Fusion is the method which conglomerates complimentary information from the source images to a single fused image . There are numerous applications of image fusion in the current scenario such as in remote sensing, medical diagnosis, machine vision system, astronomy, robotics, military units, biometrics, and surveillance. Objective: In this case multi-sensor or multi-focus devices capture images of the particular scene which are complementary in the context of information content to each other. The details from complementary images are combined through the process of fusion into a single image by applying the algorithmic formulas. The main goal of image fusion is to fetch more and proper information from the primary or source images to the fused image by minimizing the loss of details of the images and by doing so to decrease the artifacts in the final image. Methodology: In this paper, we proposed a new method to fuse the images by applying a cross bilateral filter for gray level similarities and geometric closeness of the neighboring pixels without smoothing edges. Then, the detailed images obtained by subtracting the cross bilateral filter image output from original images are being filtered through the rolling guidance filter for scale aware operation. In particular, it removes the small-scale structures while preserving the other contents of the image and successfully recovers the edges of the detailed images. Finally, the images have been fused using a weighted computed algorithm and weight normalization. Results: The results have been validated and compared with various existing state-of-the-art methods both subjectively and quantitatively. Conclusion: It was observed that the proposed method outperforms the existing methods of image fusion.

Weighted image fusion using cross bilateral filter and non-subsampled contourlet transform

2019 ◽  
Vol 30 (4) ◽  
pp. 2199-2210 ◽  
Author(s):  
M. Munawwar Iqbal Ch ◽  
M. Mohsin Riaz ◽  
Naima Iltaf ◽  
Abdul Ghafoor ◽  
Attiq Ahmad
Keyword(s):  
Image Fusion ◽  
Bilateral Filter ◽  
Contourlet Transform ◽  
Weighted Image ◽  
Cross Bilateral Filter
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