An infrared polarization image fusion algorithm based on oriented Laplacian pyramid

Image fusion algorithm is very important in image fusion process. Image fusion algorithm based on pyramid decomposition was reviewed in this paper. Pyramid decomposition algorithm mainly includes Contrast pyramid, Gradient Pyramid, Laplacian Pyramid and Ratio Pyramid. The fusion algorithms based on pyramid decomposition were respectively applied in multi-focus images, advantage and disadvantage were summarized and application was given. Fusion results were given by MATLAB simulation. Objective evaluation index including of mean, standard deviation, entropy and average gradient was calculated in this paper. Image fusion algorithm should be selected according to the information extracted and the aim of fusion.

Download Full-text

Research on Image Fusion Based on Pyramid Decomposition

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.860-863.2855 ◽

2013 ◽

Vol 860-863 ◽

pp. 2855-2858

Author(s):

Ming Jing Li ◽

Yu Bing Dong ◽

Xiao Li Wang

Keyword(s):

Image Fusion ◽

Fusion Method ◽

Laplacian Pyramid ◽

Fusion Algorithm ◽

Resolution Method ◽

Multi Scale ◽

Simulation Results ◽

Spatial Fusion

Different objects could be analyzed by use of pyramid decomposition of image. Image fusion algorithm based on pyramid decomposition of image is multi-scale, multi-resolution method. Its process is completed on different scale, different resolution and different decomposition layer. Compared with spatial fusion method, fusion effects improve obviously. In this paper, principal of pyramid decomposition and process were introduced, and simulation results of image fusion based on Laplacian pyramid, gradient pyramid, ration pyramid and contrast shows that image fusion based on pyramid decomposition is improve obviously.

Download Full-text

Image Fusion Algorithm Based on Wavelet Transform and Laplacian Pyramid

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.860-863.2846 ◽

2013 ◽

Vol 860-863 ◽

pp. 2846-2849

Author(s):

Ming Jing Li ◽

Yu Bing Dong ◽

Xiao Li Wang

Keyword(s):

Wavelet Transform ◽

Image Fusion ◽

Relevant Information ◽

Experimental Results ◽

Improve Quality ◽

Laplacian Pyramid ◽

Single Image ◽

Fusion Algorithm ◽

Fused Image

Image fusion is process which combine relevant information from two or more images into a single image. The aim of fusion is to extract relevant information for research. According to different application and characteristic of algorithm, image fusion algorithm could be used to improve quality of image. This paper complete compare analyze of image fusion algorithm based on wavelet transform and Laplacian pyramid. In this paper, principle, operation, steps and characteristic of fusion algorithm are summarized, advantage and disadvantage of different algorithm are compared. The fusion effects of different fusion algorithm are given by MATLAB. Experimental results shows that quality of fused image would be improve obviously.

Download Full-text

A visible polarization image fusion algorithm based on NSST transform

AOPC 2020: Optical Sensing and Imaging Technology ◽

10.1117/12.2579549 ◽

2020 ◽

Author(s):

Zhao Zhen Jiang ◽

Yusheng Han ◽

Fei Ye ◽

Shuaijun Ren ◽

Hao Zhai ◽

...

Keyword(s):

Image Fusion ◽

Fusion Algorithm ◽

Polarization Image

Download Full-text

Multifocus Image Fusion Using Laplacian Pyramid and Gabor Filters

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.373-375.530 ◽

2013 ◽

Vol 373-375 ◽

pp. 530-535 ◽

Cited By ~ 4

Author(s):

Chuan Zhu Liao ◽

Yu Shu Liu ◽

Ming Yan Jiang

Keyword(s):

Image Fusion ◽

High Frequency ◽

Low Frequency ◽

Gabor Filters ◽

Experimental Results ◽

Fusion Process ◽

Laplacian Pyramid ◽

Fusion Algorithm ◽

Fusion Rules

In order to get an image with every object in focus, an image fusion process is required to fuse the images under different focal settings. In this paper, a new multifocus image fusion algorithm is proposed. The algorithm is based on Laplacian pyramid and Gabor filters. The source images are decomposed by Laplacian pyramid, then the directional edges feature and detail information can be obtained by Gabor filters. Different fusion rules are applied to the low frequency and high frequency coefficients. The experimental results show that the algorithm is simple and effective.

Download Full-text

Fusion of Polarization Image Based on Curvelet Transform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.536-537.111 ◽

2014 ◽

Vol 536-537 ◽

pp. 111-114 ◽

Cited By ~ 1

Author(s):

De Xiang Zhang ◽

Hong Hai Wang ◽

Feng Xue

Keyword(s):

Image Fusion ◽

High Frequency ◽

Low Frequency ◽

Curvelet Transform ◽

Fusion Algorithm ◽

Information Measurement ◽

Multi Scale ◽

Fused Image ◽

Polarization Image ◽

Multi Scales

Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidly in the field of image fusion. Firstly, using the curvelet transform, several polarization images can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions. For the low-frequency coefficients, the average fusion method is used. For the each directional high frequency sub-band coefficients, the larger value of region variance information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused curvelet coefficients. In the present work an algorithm for image fusion based on the curvelet transform was implemented, analyzed, and compared with a wavelet-based fusion algorithm. Experimental results show that the proposed algorithm works better in preserving the edges and texture information compared with the wavelet-based image fusion algorithms.

Download Full-text