Weighted Laplacian Energy Based Image Fusion

2017 ◽  
pp. 317-326
Author(s):  
Pradeep Shankhwar ◽  
A. K. Singh ◽  
B. S. Chauhan
Keyword(s):  
Image Fusion ◽  
Laplacian Energy ◽  
Weighted Laplacian

scholarly journals A Phase Congruency and Local Laplacian Energy Based Multi-Modality Medical Image Fusion Method in NSCT Domain

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 20811-20824 ◽  
Author(s):  
Zhiqin Zhu ◽  
Mingyao Zheng ◽  
Guanqiu Qi ◽  
Di Wang ◽  
Yan Xiang
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Fusion Method ◽  
Phase Congruency ◽  
Medical Image Fusion ◽  
Laplacian Energy ◽  
Image Fusion Method

Adaptive Region-Segmentation Multi-Focus Image Fusion Based on Differential Evolution

2019 ◽  
Vol 33 (03) ◽  
pp. 1954010 ◽  
Author(s):  
Lixia Zhang ◽  
Guangping Zeng ◽  
Jinjin Wei
Keyword(s):  
Differential Evolution ◽  
Image Fusion ◽  
Experimental Result ◽  
Optimal Size ◽  
Laplacian Pyramid ◽  
Region Segmentation ◽  
Initial Decision ◽  
Laplacian Energy ◽  
Adaptive Differential Evolution ◽  
Focus Image

An adaptive region-segmentation based multi-focus image fusion method is presented using a Laplacian pyramid transform which decomposes the pre-registered source images into approximate and detail coefficients. In order to avoid the disadvantage of fixed-size blocks, the adaptive differential evolution scheme is designed to compute the optimal-size block. Firstly, with approximate coefficients, the optimal-size blocks are iteratively calculated by an adaptive differential evolution algorithm. The initial decision diagram is then completed by comparing the regional sum-modified Laplacian energy of two corresponding blocks after the regional sum-modified Laplacian energy is calculated. Secondly, the initial decision diagram is optimized by the guided image filter to obtain the final decision diagram in order to avoid the block effect of boundary. With the decision diagram, the approximate coefficients are fused using the weighted mean rules, while the detail coefficients are fused using the regional gradient energy method. Finally, an inverse Laplacian pyramid transform is used to reconstruct the fused approximate coefficients and fused detail coefficients, and to acquire the fused image where all objects are clear. The experimental result proves that the proposed method produces fusion images of fewer artifacts or additional noise, with higher computational efficiency. The proposed method is also superior to the other state-of-the-art methods in both subjective visual effect and objective quantitative evaluation indicators.

scholarly journals Side-Scan Sonar Image Fusion Based on Sum-Modified Laplacian Energy Filtering and Improved Dual-Channel Impulse Neural Network

2020 ◽  
Vol 10 (3) ◽  
pp. 1028 ◽  
Author(s):  
Ping Zhou ◽  
Gang Chen ◽  
Mingwei Wang ◽  
Xianglin Liu ◽  
Song Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Limit Function ◽  
Imperfect Detection ◽  
Side Scan Sonar ◽  
Sonar Image ◽  
Energy Filtering ◽  
Dual Channel ◽  
Visual Contrast ◽  
Laplacian Energy

The operation mode of a single strip provides incomplete side-scan sonar image in a specific environment and range, resulting in the overlapping area between adjacent strips often with imperfect detection information or inaccurate target contour. In this paper, a sum-modified Laplacian energy filtering (SMLF) and improved dual-channel pulse coupled neural network (IDPCNN) are proposed for image fusion of side-scan sonar in the domain of nonsubsampled contourlet transform (NSCT). Among them, SMLF energy is applied to extract the fusion coefficients of the low frequency sub-band, which combines the characteristics of energy information, human visual contrast, and guided filtering to eliminate the pseudo contour effect of block flow. In addition, the IDPCNN model, which utilizes the average gradient, soft limit function, and novel sum-modified Laplacian (NSML) to adaptively represent the corresponding excitation parameters, is applied to improve the depth and activity of pulse ignition, so as to quickly and accurately select the image coefficients of the high frequency sub-band. The experimental results show that the proposed method displays fine geomorphic information and clear target contour in the overlapping area of adjacent strips. The objective index values are generally optimal, which reflect the information of image edge, clarity, and overall similarity.

1528: Improved Sentinel Node Detection and Pre-Operative Planning in Prostate Cancer by Image Fusion of CT/MRI and Spect

2005 ◽  
Vol 173 (4S) ◽  
pp. 414-414
Author(s):  
Frank G. Fuechsel ◽  
Agostino Mattei ◽  
Sebastian Warncke ◽  
Christian Baermann ◽  
Ernst Peter Ritter ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Sentinel Node ◽  
Image Fusion ◽  
Sentinel Node Detection ◽  
Operative Planning

Preoperative localization of parathyroid glands

2004 ◽  
Vol 43 (03) ◽  
pp. 85-90 ◽  
Author(s):  
E. Lopez Hänninen ◽  
Th. Steinmüller ◽  
T. Rohlfing ◽  
H. Bertram ◽  
M. Gutberlet ◽  
...  
Keyword(s):  
Image Fusion ◽  
Single Photon ◽  
Imaging Techniques ◽  
Photon Emission ◽  
Parathyroid Glands ◽  
Preoperative Localization ◽  
Mri Findings ◽  
99Mtc Mibi ◽  
Weighted Sequences ◽  
Mibi Scintigraphy

Summary Aim: Minimally invasive resection of hyperfunctional parathyroid glands is an alternative to open surgery. However, it requires a precise preoperative localization. This study evaluated the diagnostic use of magnetic resonance (MR) imaging, parathyroid scintigraphy, and consecutive image fusion. Patients, methods: 17 patients (9 women, 8 men; age: 29-72 years; mean: 51.2 years) with primary hyperparathyroidism were included. Examination by MRI used unenhanced T1- and T2-weighted sequences as well as contrast-enhanced T1-weighted sequences. 99mTc-MIBI scintigraphy consisted of planar and SPECT (single photon emission tomography) imaging techniques. In order to improve the anatomical localization of a scintigraphic focus, SPECT-data were fused with the corresponding MR-data using a modified version of the Express 5.0 software (Advanced Visual Systems, Waltham, MA). Results of image fusion were then compared to histopathology. Results: In 14/17 patients, a single parathyroid adenoma was found. There were 3 cases with hyperplastic glands. MRI detected 10 (71%), scintigraphy 12 (86%) adenomas. Both modalities detected 1/3 patients with hyperplasia. Image fusion improved the anatomical assignment of the 13 scintigraphic foci in five patients and was helpful in the interpretation of inconclusive MR-findings in two patients. Conclusions: Both MRI and 99mTc-MIBI scintigraphy sensitively detect parathyroid adenomas but are less reliable in case of hyperplastic glands. In case of a scintigraphic focus, image fusion considerably improves its topographic assignment. Furthermore, it facilitates the evaluation of inconclusive MRI findings.

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