A curvelet-based multi-sensor image denoising for KLT-based image fusion

Author(s):  
Amit Vishwakarma ◽  
M. K. Bhuyan
Keyword(s):  
Computers ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 129
Author(s):  
Guanqiu Qi ◽  
Gang Hu ◽  
Neal Mazur ◽  
Huahua Liang ◽  
Matthew Haner

Multi-modality image fusion applied to improve image quality has drawn great attention from researchers in recent years. However, noise is actually generated in images captured by different types of imaging sensors, which can seriously affect the performance of multi-modality image fusion. As the fundamental method of noisy image fusion, source images are denoised first, and then the denoised images are fused. However, image denoising can decrease the sharpness of source images to affect the fusion performance. Additionally, denoising and fusion are processed in separate processing modes, which causes an increase in computation cost. To fuse noisy multi-modality image pairs accurately and efficiently, a multi-modality image simultaneous fusion and denoising method is proposed. In the proposed method, noisy source images are decomposed into cartoon and texture components. Cartoon-texture decomposition not only decomposes source images into detail and structure components for different image fusion schemes, but also isolates image noise from texture components. A Gaussian scale mixture (GSM) based sparse representation model is presented for the denoising and fusion of texture components. A spatial domain fusion rule is applied to cartoon components. The comparative experimental results confirm the proposed simultaneous image denoising and fusion method is superior to the state-of-the-art methods in terms of visual and quantitative evaluations.


2005 ◽  
Vol 173 (4S) ◽  
pp. 414-414
Author(s):  
Frank G. Fuechsel ◽  
Agostino Mattei ◽  
Sebastian Warncke ◽  
Christian Baermann ◽  
Ernst Peter Ritter ◽  
...  

2004 ◽  
Vol 43 (03) ◽  
pp. 85-90 ◽  
Author(s):  
E. Lopez Hänninen ◽  
Th. Steinmüller ◽  
T. Rohlfing ◽  
H. Bertram ◽  
M. Gutberlet ◽  
...  

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.


2019 ◽  
Vol 2019 (2) ◽  
pp. 187-1-187-6
Author(s):  
Fayez Lahoud ◽  
Sabine Süsstrunk

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