The Wavelet Transform for Image Processing Applications

Bouden, Toufik; Mokhtar, Norrima

doi:10.5772/35982

Cited by 22 publications

(13 citation statements)

References 53 publications

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“…ere are many notable works on wavelets and applications of wavelet transforms [32][33][34]. We focused our survey on works of wavelet transform applied in the eld of quantum information processing, i.e., quantum wavelet transforms (QWT).…”

Section: Quantum Wavelet Transformmentioning

confidence: 99%

Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer

El-Araby

2019

International Journal of Reconfigurable Computing

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The high resolution of multidimensional space-time measurements and enormity of data readout counts in applications such as particle tracking in high-energy physics (HEP) is becoming nowadays a major challenge. In this work, we propose combining dimension reduction techniques with quantum information processing for application in domains that generate large volumes of data such as HEP. More specifically, we propose using quantum wavelet transform (QWT) to reduce the dimensionality of high spatial resolution data. The quantum wavelet transform takes advantage of the principles of quantum mechanics to achieve reductions in computation time while processing exponentially larger amount of information. We develop simpler and optimized emulation architectures than what has been previously reported, to perform quantum wavelet transform on high-resolution data. We also implement the inverse quantum wavelet transform (IQWT) to accurately reconstruct the data without any losses. The algorithms are prototyped on an FPGA-based quantum emulator that supports double-precision floating-point computations. Experimental work has been performed using high-resolution image data on a state-of-the-art multinode high-performance reconfigurable computer. The experimental results show that the proposed concepts represent a feasible approach to reducing dimensionality of high spatial resolution data generated by applications such as particle tracking in high-energy physics.

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Section: Quantum Wavelet Transformmentioning

confidence: 99%

Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer

El-Araby

2019

International Journal of Reconfigurable Computing

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“…In this study one level of DWT decomposition is applied and the threshold value is compared against all the pixels at each detail bands (H, V, and D). Therefore, a good threshold value would lead to less distortion of the image [3,5,7]. Where: : The standard deviation (STD) m : the mean n : the number of pixels in the sub-bands xi : sub-band.…”

Section: Proposed De-noising Schemementioning

confidence: 99%

Image Denoising by Median Filter in Wavelet Domain

Ramadhan¹,

Mahmood²,

Elçi³

2017

IJMA

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“…The shape of the wavelet allows representing different detail or resolution [17]. Now a days, wavelet transform is being increasingly used not only in the field of image and signal processing applications but also in many other different areas ranging from mathematics, physics, astronomy to statistics and economics [14,19].…”

Section: B Steganography Based On Domain Typementioning

confidence: 99%

Steganography and classification of image steganography techniques

Kaur

Bansal

2014

2014 International Conference on Computing for Sustainable Global Development (INDIACom)

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Information is wealth of any organization and in present era in which information transferred through digital media and internet, it became a top priority for any organizations to protect this wealth. Whatever technique we adopt for the security purpose, the degree and level of security always remains top concern. Steganography is one such technique in which presence of secret message cannot be detected and we can use it as a tool for security purpose to transmit the cofidential information in a secure way. It is an ongoing research area having vast number of applications in distinct fields such as defense and intelligence, medical, on-line banking, on-line transaction, to stop music piracy and other financial and commercial purposes. There are various steganography approaches exist and they differs depending upon message to be embedded, use of file type as carrier or compression method used etc. The focus of this paper is to classify distinct image steganography techniques besides giving overview, importance and challenges of steganography techniques. Other related security techniques are also been discussed in brief in this paper. The classification of steganography techniques may provide not only understanding and guidelines to researchers in this field but also provide directions for future work in this field.

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The Wavelet Transform for Image Processing Applications

Cited by 22 publications

References 53 publications

Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer

Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer

Image Denoising by Median Filter in Wavelet Domain

Steganography and classification of image steganography techniques

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