Wavelet transform applications

Kulkarni, Jyoti

doi:10.1109/icectech.2011.5941550

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…Wavelet theory has been developed to a significant degree since the beginning of the last century. It was first applied in signal processing during the 1980 s and it has been recognized as a great potential theory in the image processing fields over the last few decades [13,14]. Wavelet transform provides a better image fusion performance because of advantages such as pyramid decomposition, but also because it has the properties of multi-resolution, spatial and frequency localization [15].…”

Section: Introductionmentioning

confidence: 99%

An image fusion algorithm based on lifting wavelet transform

Wang

Shen

Zhou

et al. 2015

J. Opt.

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The directional characteristic of the low-frequency and high-frequency coefficients based on the wavelet transform for original images is discussed and analyzed, and a novel image fusion algorithm based on the lifting wavelet transform is proposed in this paper. Firstly, the source images are transformed to the frequency domain by means of the lifting wavelet. Then, the resultant coefficients of the low-frequency sub-band are achieved by comparing the covariance of the coefficients of different images. Meanwhile, the resultant coefficients of each high-frequency sub-band are calculated according to the matching measure between the directional characteristic of the coefficients in the same sub-band and the quad-tree structure relationship of the coefficients with the same direction in different sub-bands. At last, the fusion-resultant image is obtained through the reversely lifting wavelet transformation. Several evaluation indexes, such as entropy, average grads, PSNR and RMSE, are employed to judge the experimental images with different fusion methods. The comparison results show that the proposed method image fusion algorithm based on the lifting wavelet transform is better than conventional methods, and has much application value.

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Section: Introductionmentioning

confidence: 99%

An image fusion algorithm based on lifting wavelet transform

Wang

Shen

Zhou

et al. 2015

J. Opt.

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“…The use of modulation coefficients in the HPM equals the proportion among the LRPI and the LRMIs. The corresponding precise approach is expressed in [92].…”

Section: High-pass Modulationmentioning

confidence: 99%

Image Fusion Methods: A Survey

Masood¹,

Sharif²,

Yasmin³

et al. 2017

JESTR

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Image fusion is an approach which is used to amalgamate the corresponding features in a sequence of input images to a single composite image that preserves all the significant features of the input images. Image fusion is also known as pansharpening. It is a method which is used to integrate and add the geometric detail of a high-resolution panchromatic (Pan) image and the information of color of a low-resolution multispectral (MS) image for the production of a high-resolution MS image. This methodology is mainly most important and significant for any large-scale applications. Image fusion classification based on its systems (models and algorithms) are considered and overviewed in this survey. The basic two algorithms categories are analyzed and compared to each other, in the analysis and discussion section the major points to be considered while performing image fusion are highlighted.

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