scholarly journals A Hybrid Method for Multi-Focus Image Fusion Based on Fast Discrete Curvelet Transform

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 14898-14913 ◽  
Author(s):  
Yong Yang ◽  
Song Tong ◽  
Shuying Huang ◽  
Pan Lin ◽  
Yuming Fang
Keyword(s):  
Image Fusion ◽  
Hybrid Method ◽  
Curvelet Transform ◽  
Focus Image ◽  
Fast Discrete Curvelet Transform

scholarly journals Multi-Focus Image Fusion with Multi-Scale Transform Optimized by Metaheuristic Algorithms

2021 ◽  
Vol 38 (2) ◽  
pp. 247-259
Author(s):  
Asan Ihsan Abas ◽  
Nurdan Akhan Baykan
Keyword(s):  
Image Fusion ◽  
Curvelet Transform ◽  
Bat Algorithm ◽  
Single Image ◽  
Image Capture ◽  
Multi Scale ◽  
Optimal Weights ◽  
Fusion Methods ◽  
Low Pass ◽  
Focus Image

Focus is limited and singular in many image capture devices. Therefore, different focused objects at different distances are obtained in a single image taken. Image fusion can be defined as the acquisition of multiple focused objects in a single image by combining important information from two or more images into a single image. In this paper, a new multi-focus image fusion method based on Bat Algorithm (BA) is presented in a Multi-Scale Transform (MST) to overcome limitations of standard MST Transform. Firstly, a specific MST (Laplacian Pyramid or Curvelet Transform) is performed on the two source images to obtain their low-pass and high-pass bands. Secondly, optimization algorithms were used to find out optimal weights for coefficients in low-pass bands to improve the accuracy of the fusion image and finally the fused multi-focus image is reconstructed by the inverse MST. The experimental results are compared with different methods using reference and non-reference evaluation metrics to evaluate the performance of image fusion methods.

Multi-Focus Image Fusion Using Curvelet Transform

2013 ◽  
Vol 347-350 ◽  
pp. 2743-2746
Author(s):  
Yong Li
Keyword(s):  
Image Fusion ◽  
Curvelet Transform ◽  
Fusion Rules ◽  
Curve Edge ◽  
Focus Image

Curvelet transform is a new muiti-scale geometic analysis, which has the characteristics of anisotropy. It is more suitable for the analysis of image curve edge characteristics than wavelet. Thus, in this paper it is applied to multi-focus image fusion, and used fusion rules that suitable for the characteristics of multi-focus image fusion.

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