Image Fusion Algorithm Based on Two-Dimensional Discrete Wavelet Transform and Spatial Frequency

2010 ◽  
Author(s):  
Zhongxian Qu ◽  
Jingbo Zhang ◽  
Zijun Feng
Keyword(s):  
Wavelet Transform ◽  
Spatial Frequency ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Fusion Algorithm

scholarly journals Performance of Spatial Frequency Discrete Wavelet Transform Based Remote Sensing Image Fusion Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 7968-7978
Keyword(s):  
Remote Sensing ◽  
Wavelet Transform ◽  
Spatial Frequency ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Fusion Algorithm ◽  
Fusion Technique ◽  
Image Fusion Technique ◽  
Better Than

The high sensor cost for producing images with superior spectral and spatial qualities in remote sensing application have led to the development of image fusion algorithms. Image fusion technique combines a Panchromatic image and a Multispectral image with an aim to produce images with excellent spatial and spectral qualities. One of the major factors that affect the performance of any image fusion algorithm is the capability of the algorithm in extracting the spatial and spectral data from the respective images and how effective the so extracted information is blended together. One of the recently developed spectral domain algorithm to perform image fusion in remote sensing applications is Spatial Frequency Discrete Wavelet Transform abbreviated as SFDWT. The excellence of SFDWT image fusion algorithm is already proven better than the prevailing algorithms based on Discrete Wavelet Transform. This paper is coined with an eye to realize the performance of SFDWT based image fusion algorithm with respect to IHS-DWT, which being an enhanced form of a typical DWT based image fusion algorithm. The performance of SFDWT and IHS-DWT based image fusion algorithms will be evaluated by applying both techniques in the fusion of urban images received from Pléiades sensors with 1:4 resolution ratio using qualitative and quantitative image quality assessment methods. The consequence of varying the decomposition level on the quality of the images produced using SFDWT image fusion technique and three variants of IHS-DWT techniques based on substitution, averaging and maximum selection will be also evaluated. From the experimental analysis done using MATLAB simulation, it will be vivid that images obtained using image fusion algorithm based on SFDWT are much better than that obtained using IHS-DWT technique with excellent spatial and spectral qualities

Multi-Focus Image Fusion Using Local Energy Pattern

2011 ◽  
Vol 145 ◽  
pp. 119-123
Author(s):  
Ko Chin Chang
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Local Energy ◽  
View Point ◽  
Fusion Algorithm ◽  
Image Capture ◽  
Focus Image ◽  
Better Than

For general image capture device, it is difficult to obtain an image with every object in focus. To solve the fusion issue of multiple same view point images with different focal settings, a novel image fusion algorithm based on local energy pattern (LGP) is proposed in this paper. Firstly, each focus images is decomposed using discrete wavelet transform (DWT) separately. Secondly, to calculate LGP with the corresponding pixel and its surrounding pixels, then use LGP to compute the new coefficient of the pixel from each transformed images with our proposed weighted fusing rules. The rules use different operations in low-bands coefficients and high-bands coefficients. Finally, the generated image is reconstructed from the new subband coefficients. Moreover, the reconstructed image can represent more detailed for the obtained scene. Experimental results demonstrate that our scheme performs better than the traditional discrete cosine transform (DCT) and discrete wavelet transform (DWT) method in both visual perception and quantitative analysis.

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