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Multisensor Image Fusion Using the Wavelet Transform
CVGIP: Graphical Models and Image Processing, 1995The goal of image fusion is to integrate complementary information from multisensor data such that the new images are more suitable for the purpose of human visual perception and computer-processing tasks such as segmentation, feature extraction, and ...
Hui Li, B. S. Manjunath, S. Mitra
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Discrete Wavelets and Fast Wavelet Transform
1991The wavelet analysis, introduced by J. MORLET and Y. MEYER in the middle of the eighties, is a processus of time-frequency (or time-scale) analysis which consists of decomposing a signal into a basis of functions (o jk ) called wavelets. These wavelets are in turn deduced from the analyzing wavelet o by dilatations and translations. More precisely:
Bonnet, Pierre, Rémond, Didier
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Journal of Real-Time Image Processing, 2010
There has been an increasing concern for the security of multimedia transactions over real-time embedded systems. Partial and selective encryption schemes have been proposed in the research literature, but these schemes significantly increase the computation cost leading to tradeoffs in system latency, throughput, hardware requirements and power usage.
Joseph Zambreno, Amit Pande
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There has been an increasing concern for the security of multimedia transactions over real-time embedded systems. Partial and selective encryption schemes have been proposed in the research literature, but these schemes significantly increase the computation cost leading to tradeoffs in system latency, throughput, hardware requirements and power usage.
Joseph Zambreno, Amit Pande
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2017
Historically, the concept of wavelets started to appear more frequently only in the early 1980s. This new concept can be viewed as a synthesis of various ideas originating from different disciplines including mathematics, physics, and engineering. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform
Lokenath Debnath, Firdous A. Shah
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Historically, the concept of wavelets started to appear more frequently only in the early 1980s. This new concept can be viewed as a synthesis of various ideas originating from different disciplines including mathematics, physics, and engineering. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform
Lokenath Debnath, Firdous A. Shah
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Applied Optics, 1997
The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc.
Javier Garcia +4 more
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The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc.
Javier Garcia +4 more
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Symplectic wavelet transformation
Optics Letters, 2006Usually a wavelet transform is based on dilated-translated wavelets. We propose a symplectic-transformed-translated wavelet family psi(*)(r,s)(z-kappa) (r,s are the symplectic transform parameters, |s|(2)-|r|(2)=1, kappa is a translation parameter) generated from the mother wavelet psi and the corresponding wavelet transformation W(psi)f(r,s;kappa ...
Hai-Liang Lu, Hong-Yi Fan
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Phase Retrieval for the Cauchy Wavelet Transform
arXiv.org, 2014We consider the phase retrieval problem in which one tries to reconstruct a function from the modulus of its wavelet transform. We study the uniqueness and stability of the reconstruction. In the case where the wavelets are Cauchy wavelets, we prove that
S. Mallat, Irène Waldspurger
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2015
In this chapter we will introduce the wavelet transform with the purpose of obtaining better representation of functions using atomic decompositions in the time-frequency domain.
Jonas Gomes, Luiz Velho
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In this chapter we will introduce the wavelet transform with the purpose of obtaining better representation of functions using atomic decompositions in the time-frequency domain.
Jonas Gomes, Luiz Velho
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2002
We mentioned in the introduction to Part D the shortcomings of the windowed Fourier transform. This chapter gives another approach to the time-frequency issue of Fourier analysis. The role played in the windowed Fourier transform by the family of functions $${\omega _{v,b}}(t) = \omega (t - b){e^{ + 2i\pi vt}},\quad b,v \in \mathbb{R}$$ is ...
Pierre Brémaud, Pierre Brémaud
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We mentioned in the introduction to Part D the shortcomings of the windowed Fourier transform. This chapter gives another approach to the time-frequency issue of Fourier analysis. The role played in the windowed Fourier transform by the family of functions $${\omega _{v,b}}(t) = \omega (t - b){e^{ + 2i\pi vt}},\quad b,v \in \mathbb{R}$$ is ...
Pierre Brémaud, Pierre Brémaud
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2011
The concept of a transform was introduced in Section 24.1 and the rest of Chapter 24 discusses orthogonal transforms. The transforms dealt with in this chapter are different and are referred to as subband transforms, because they partition an image into various bands or regions that contain different features of the image.
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The concept of a transform was introduced in Section 24.1 and the rest of Chapter 24 discusses orthogonal transforms. The transforms dealt with in this chapter are different and are referred to as subband transforms, because they partition an image into various bands or regions that contain different features of the image.
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