Multi-focus Image Fusion Based on Stationary Wavelet Transform and Extended Spatial Frequency Measurement

Borwonwatanadelok, Pusit; Rattanapitak, Wirat; Udomhunsakul, Somkait

doi:10.1109/icect.2009.94

Cited by 34 publications

(28 citation statements)

References 9 publications

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“…Fig.3.a,b,c,d, and e shows the fusion results obtained via Stationary Wavelet Transform (SWT) based [1,2], Spatial Frequency (SF) based [5], combined SWT and SF (SWT-SF) [6], Lattice Filters based [4] and combined Lattice and SF based methods , respectively. It can be concluded from the resulting images that the spatial resolution of the initial MS images appear to have been enhanced.…”

Section: A Visual Analysismentioning

confidence: 99%

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A new subband domain method for spatial frequency based image fusion

Kaplan

Erer

2011

Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011

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A new image fusion algorithm, based on lattice filters and spatial frequency, to merge ERS and multispectral SPOT data is presented. First, ERS and SPOT data are decomposed into their subbands with analysis lattice filter structure. The detail subbands are decomposed into blocks, and these blocks are merged according to a predefined Spatial Frequency based rule. Finally, the fused image is obtained by synthesis lattice filter structure.

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Section: A Visual Analysismentioning

confidence: 99%

“…Recently, a new method which combines the wavelet transform based method with Spatial Frequency Measures (SFM) is proposed [6]. In this method, two source images are decomposed into four subbands (LL, LH, HL and HH subbands) by stationary wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

A new subband domain method for spatial frequency based image fusion

Kaplan

Erer

2011

Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011

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“…In the recent years multi-resolution approaches using Mallat [7], the à trous [8] transforms, contourlet [9]- [10] have been proposed for image fusion. Fusion approaches employing wavelets analysis include transforms such as SWT [11], LWT [12], MWT [12], RDWT [13], and complex wavelet [4]. B. Yang et al [14] implemented the pixel level decomposition on weighted average fusion rule.…”

Section: Introductionmentioning

confidence: 99%

Medical image fusion using combination of PCA and wavelet analysis

Krishn

Bhateja

Himanshi

et al. 2014

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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Medical image fusion for merging of complementary diagnostic content has been carried out in this paper using Principal Component Analysis (PCA) and Wavelets. The proposed fusion approach involves sub-band decomposition using 2D-Discrete Wavelet Transform (DWT) in order to preserve both spectral and spatial information. Further, PCA is applied on the decomposed coefficients to maximize the spatial resolution. An optimal variant of the daubechies wavelet family has been selected experimentally for better fusion results. Simulation results demonstrate an improvement in visual quality of the fused image in comparison to other state-of-art fusion approaches.

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“…Stationary wavelet transform (SWT) [1] is modified DWT where this drawback is removed by removing the down samplers and up samplers in DWT and up sampling the filter coefficients by a factor of 2(j-1)in the jth level of the algorithm. Borwonwatanadelok et al [32] , Somkait et al [33] and kannan et al [34] have shown that This method provides good result at level 2 of decomposition but it is very time consuming.…”

Section: Stationary Wavelet Transform (Swt) Based Image Fusionmentioning

confidence: 99%

“…Stationary Wavelet Transform(SWT) [32][33][34] This method provides good result at level2 of decomposition It is time consuming…”

Section: International Journal Of Computer Applications (0975 -8887)mentioning

confidence: 99%

Image Fusion Techniques: A Review

Mishra¹,

Palkar²

2015

IJCA

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Image Fusion is used to retrieve important data from a set of input images and put it into a single output image to make it more informative and useful than any of the input images. It improves quality and applicability of data. Quality of the fused image depends on the application. Image fusion is widely used in intelligent robots, stereo camera fusion, medical imaging, and manufacture process monitoring, electronic circuit design and inspection, complex machine/device diagnostics and in intelligent robots on assembly lines. This paper presents a literature review on various spatial and frequency domain image fusion techniques such as averaging, min-max, block replace, HIS,PCA, brovey, pyramid based and transform based techniques. Various quality measures have been discussed to perform quantitative comparison of these methods.

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Multi-focus Image Fusion Based on Stationary Wavelet Transform and Extended Spatial Frequency Measurement

Cited by 34 publications

References 9 publications

A new subband domain method for spatial frequency based image fusion

A new subband domain method for spatial frequency based image fusion

Medical image fusion using combination of PCA and wavelet analysis

Image Fusion Techniques: A Review

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