Multifocus Noisy Image Fusion Algorithm Using the Contourlet Transform

t is mostly difficult to get an image that contains all relevant objects in focus, because of the limited depth-of-focus of optical lenses. The multifocus image fusion method can solve the problem effectively. Nonsubsampled Contourlet transform has varying directions and multiple scales. When the Nonsubsampled contourlet transform is introduced to image fusion, the characteristics of original images are taken better and more information for fusion is obtained. A new method of multi-focus image fusion based on Nonsubsampled contourlet transform (NSCT) with the fusion rule of region statistics is proposed in this paper. Firstly, different focus images are decomposed using Nonsubsampled contourlet transform. Then low-bands are integrated using the weighted average, high-bands are integrated using region statistics rule. Next the fused image will be obtained by inverse Nonsubsampled contourlet transform. Finally the experimental results are showed and compared with those of method based on Contourlet transform. Experiments show that the approach can achieve better results than the method based on contourlet transform.

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Contourlet Transform in the Application of the Image Fusion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.239-240.1432 ◽

2012 ◽

Vol 239-240 ◽

pp. 1432-1436

Author(s):

Zhuan Zheng Zhao

Keyword(s):

Image Fusion ◽

Image Resolution ◽

Contourlet Transform ◽

Fusion Method ◽

Fusion Algorithm ◽

Fused Image ◽

New Interpretation ◽

Image Fusion Method

Image Fusion is integrating two or more sensors at the same time or at different times of image or videos equenece to generate a new interpretation of this scene. Its main purpose is increasing reliability or image resolution by redueing uncertainty through redundancy of different images.In this paper, a image fusion method based on contourlet transform is presented. The algorithm can fuse corresponding information in different resolutions and directions, which makes the fused image clearer and more abundant in details. Meanwhile, because of the fuzzy logic’s capacity of resolving uncertain problems, it overcomes the drawbacks of traditional fusion algorithm based on contourlet transform, and integrates as much information as possible into the fused image.

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Multi-focus Image Fusion Algorithm Based on Motivated Pulse Coupled Neural Networks Using Nonsubsampled Contourlet Transform

DEStech Transactions on Computer Science and Engineering ◽

10.12783/dtcse/cmsam2017/16434 ◽

2017 ◽

Author(s):

Lin BAI ◽

Meng-yun JIANG ◽

Zhi-tong HUANG ◽

Miao-lan GONG

Keyword(s):

Neural Networks ◽

Image Fusion ◽

Contourlet Transform ◽

Nonsubsampled Contourlet Transform ◽

Fusion Algorithm ◽

Coupled Neural Networks ◽

Focus Image ◽

Pulse Coupled Neural Networks

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An Image Fusion Algorithm based on Modified Contourlet Transform

International Journal of Circuits, Systems and Signal Processing ◽

10.46300/9106.2020.14.46 ◽

2020 ◽

Vol 14 ◽

Keyword(s):

Image Fusion ◽

Finite Depth ◽

Contourlet Transform ◽

Translation Invariance ◽

Fusion Algorithm ◽

Multi Scale ◽

Directional Filter ◽

Fusion Methods ◽

Focus Image ◽

Combining Information

Multi-focus image fusion has established itself as a useful tool for reducing the amount of raw data and it aims at overcoming imaging cameras’ finite depth of f ield by combining information from multiple images with the same scene. Most of existing fusion algorithms use the method of multi-scale decompositions (MSD) to fuse the s ource images. MSD-based fusion algorithms provide much better performance than the conventional fusion methods .In the image fusion algorithm based on multi-scale decomposition, how to make full use of the characteristics of coefficients to fuse images is a key problem.This paper proposed a modified contourlet transform(MCT) based on wavelets and nonsubsampled directional filter banks(NSDFB). The image is decomposed in wavelet domain,and each highpass subband of wavelets is further decomposed into multiple directional subbands by using NSDFB. The MCT has the important features of directionality and translation invariance. Furthermore, the MCT and a novel region energy strategy are exploited to perform image fusion algorithm. simulation results shows that the proposed method can the fusion results visually and also improve in objective evaluating parameters.

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