- Tytuł:
- Riesz-Laplace Wavelet Transform and PCNN Based Image Fusion
- Autorzy:
-
Sun, Shuifa
Tang, Yongheng
Mei, Zhoujunshen
Yang, Min
Tang, Tinglong
Wu, Yirong - Powiązania:
- https://bibliotekanauki.pl/articles/2204258.pdf
- Data publikacji:
- 2023
- Wydawca:
- Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Instytut Informatyki Technicznej
- Tematy:
-
image fusion
Riesz transforms
polyharmonic spline
Laplacian wavelet
pulse-coupled neural networks
PCNN - Opis:
- Important information perceived by human vision comes from the low-level features of the image, which can be extracted by the Riesz transform. In this study, we propose a Riesz transform based approach to image fusion. The image to be fused is first decomposed using the Riesz transform. Then the image sequence obtained in the Riesz transform domain is subjected to the Laplacian wavelet transform based on the fractional Laplacian operators and the multi-harmonic splines. After Laplacian wavelet transform, the image representations have directional and multi-resolution characteristics. Finally, image fusion is performed, leveraging Riesz-Laplace wavelet analysis and the global coupling characteristics of pulse coupled neural network (PCNN). The proposed approach has been tested in several application scenarios, such as multi-focus imaging, medical imaging, remote sensing full-color imaging, and multi-spectral imaging. Compared with conventional methods, the proposed approach demonstrates superior performance on visual effects, contrast, clarity, and the overall efficiency.
- Źródło:
-
Machine Graphics & Vision; 2023, 32, 1; 73--84
1230-0535
2720-250X - Pojawia się w:
- Machine Graphics & Vision
- Dostawca treści:
- Biblioteka Nauki
Artykuł