An efficient non-separable architecture for Haar wavelet transform with lifting structure

Bamerni, Serwan Ali; Al-Sulaifanie, Ahmed Khorsheed

doi:10.1016/j.micpro.2019.102881

Cited by 12 publications

(8 citation statements)

References 12 publications

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“…The NSHWT [18] is an alternative to the traditional DWT for 2-dimensional (2D) signals. DWT on 2D signals is usually done in two steps, by doing the 1-dimensional transform row-by-row, followed by column-by-column to obtain four sub-bands, LL, LH, HL, HH.…”

Section: Modified Non-separable Haar Wavelet Transformmentioning

confidence: 99%

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Non-blind Image Watermarking Algorithm based on Non-Separable Haar Wavelet Transform against Image Processing and Geometric Attacks

Razak

Abdullah

Halim

2023

ARASET

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The protection of digital media become crucial and needs to be developed as technology continues to become more advanced. This is to cater to the problems in copyright protection and data security. This paper presents a new non-blind image watermarking algorithm applying modified non-separable Haar wavelet transform (NSHWT), singular value decomposition (SVD), Arnold’s cat map and Rabin-p cryptosystem. The traditional transform domain watermarking (DWT) is resource-consuming, especially when performed on large image data. In order to improve on this issue, the proposed algorithm applied the modified NSHWT, a much more efficient alternative to the DWT. Another concern of digital watermarking algorithms is it is often publicly known, so encryptions are important to keep the image secure. The embedded watermark image is protected by scrambling the image using Arnold’s cat map, and the scrambling parameters are encrypted with the Rabin-p cryptosystem to keep the algorithm secure. In general, the application of modified NSHWT and SVD makes the watermark highly robust against image processing and geometric processing attacks, and its security is ensured with the protection by Arnold’s cat map and Rabin-p cryptosystem. There are already many algorithms with high imperceptibility and robustness, but in finding the perfect balance, authors often forsake other metrics such as efficiency, security, and flexibility. These are also essential when the algorithm is considered in real applications. Thus, the proposed algorithm is evaluated in terms of imperceptibility, robustness, and efficiency. The algorithm achieved imperceptibility results of 51.5157 average PSNR and 0.9991 average SSIM, and robustness results from 0.9710 to 0.9966 NC values. The algorithm is also around 40% faster to execute with modified NSHWT compared to the traditional DWT. Finally, it has a high embedding capacity of 6 bits per pixel. Overall, results show that the algorithm is highly imperceptible and robust against image processing and geometric attacks, while additionally being secure and flexible.

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Section: Modified Non-separable Haar Wavelet Transformmentioning

confidence: 99%

“…The NSHWT calculates all sub-bands in one step, by going through the signal by 2 × 2 blocks, hence the "non-separable" in its name. This method has the advantage of not requiring transposition and frame memory during calculation [18].…”

Section: Modified Non-separable Haar Wavelet Transformmentioning

confidence: 99%

Non-blind Image Watermarking Algorithm based on Non-Separable Haar Wavelet Transform against Image Processing and Geometric Attacks

Razak

Abdullah

Halim

2023

ARASET

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“…Transform domain techniques generally have much higher time complexity and computation costs compared to spatial domain techniques. Although the DWT has the downsampling process that makes it more efficient, it requires high transposition memory, reaching at least 2N for a square matrix of order N [6]. The NSHWT is a method to perform the DWT technique on 2-D signals more efficiently, by removing the need for transposition memory during calculations [6].…”

Section: Main Contributionsmentioning

confidence: 99%

“…The non-separable Haar wavelet transform (NSHWT) and SVD are applied to cover those weaknesses. The NSHWT [6] is a faster and more efficient alternative to the DWT. The NSHWT has significant advantages over the DWT in hardware utilization, maximum speed, power consumption.…”

Section: Introductionmentioning

confidence: 99%

Robustness of Modified Non-Separable HaarWavelet Transform and Singular Value Decomposition for Non-blind Digital Image Watermarking

Razak¹,

Abdullah²,

Halim³

2022

MJMS

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Security is a matter of significant concern for image media. An effective way to protect images is by digital watermarking. This paper introduces a non-blind digital watermarking scheme using modified non-separable Haar wavelet transform (NSHWT), singular value decomposition (SVD), Arnold's cat map, and Rabin-p cryptosystem to embed a binary watermark image into a color cover image. Aside from robustness, security is also prioritized in the scheme. High robustness is achieved using two transform domain techniques, discrete wavelet transform (DWT) and SVD, while security is heightened with the double encryption by Arnold's cat map scrambling and Rabin-p cryptosystem. A disadvantage of the discrete wavelet transform in digital image watermarking is the calculation complexity and the high cost of changing memory and time. The proposed algorithm uses a modified NSHWT instead of the traditional method of DWT. Therefore, the load of the process on the hardware can significantly be reduced while still maintaining the advantages of DWT. The algorithm is objectively evaluated in terms of imperceptibility, robustness, and embedding capacity for both binary and color watermarks, as well as efficiency. It has been concluded that the proposed scheme performs competently compared with other recent watermarking techniques based on DWT and SVD.

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“…The consumed power for each system is affected by many aspects, including system frequency, density of resources, connection topology, and the level of supply voltage [25]. As in all embedded systems, the power consumption is made up of two parts, the dynamic power and static power.…”

Section: Consumed Powermentioning

confidence: 99%

Field programmable gate arrays implementation of different standard deviation estimation techniques

Bamerni

Alsulaifanie

2022

IJEECS

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Additive white Gaussian noise level estimation has found its application in many fields such as biomedical signal processing, communication system, and image processing. Many methods have been proposed with different output accuracy, system complexity, power consumption, and speed. In this paper, three of the most well-known and largely used algorithms (median based, root mean square (RMS) based, and P84 based methods) have been implemented and investigated in a full comparison between them to find their advantage and disadvantage, and the suitability of each method for a specific application. The three designs are created using Xilinx system generator (XSG) and implemented on Xilinx field programmable gate arrays (FPGA) development board with Zynq series "XC7Z020-1CLG484", to evaluate the design's performance and the results are discussed in the paper.

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An efficient non-separable architecture for Haar wavelet transform with lifting structure

Cited by 12 publications

References 12 publications

Non-blind Image Watermarking Algorithm based on Non-Separable Haar Wavelet Transform against Image Processing and Geometric Attacks

Non-blind Image Watermarking Algorithm based on Non-Separable Haar Wavelet Transform against Image Processing and Geometric Attacks

Robustness of Modified Non-Separable HaarWavelet Transform and Singular Value Decomposition for Non-blind Digital Image Watermarking

Field programmable gate arrays implementation of different standard deviation estimation techniques

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