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Software design and FPGA implementation of optimized medical image fusion techniques

Multimedia Tools and applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

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Enhanced security framework for medical data embedding based on octonionic steganographic transforms and FPGA-accelerated integrity verification

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Alexandria Engineering Journal 2025年 125卷 480-495页

作者： Tahiri, Mohamed Amine Karmouni, Ilham Mchichou, Ismail Bencherqui, Ahmed El Maloufy, Ahmed Karmouni, Hicham Moustabchir, Hassane Sayyouri, Mhamed Khafaga, Doaa Sami Aldakheel, Eman Abdullah Abouhawwash, Mohamed Engineering Systems and Applications Laboratory National School of Applied Sciences Sidi Mohamed Ben Abdellah University Fez Morocco Laboratory of Electronic Signals and Systems of Information Sidi Mohamed Ben Abdellah University Fez Morocco National School of Applied Sciences Cadi Ayyad University Marrakech Morocco Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O.Box 84428 Riyadh11671 Saudi Arabia Department of Industrial and Systems Engineering King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

This study suggests a novel approach that combines steganography with innovative image and signal processing techniques to enhance the security and integrity of medical images. We employ octonions, which offer a rich and high-fidelity representation, to encode two medical images. Racah orthogonal polynomials (DORPs), which extract distinctive visual properties and are thus perfect for data concealment, are added to this method to improve it further. We created a verification method utilizing the SHA-256 hashing technique to guarantee data integrity. To identify any manipulation, this method computes the steganographic image's hash both before and after transmission. We used an FPGA-based technology to improve this process, which uses parallel processing to greatly speed up hash computations compared to conventional software techniques. Discrete wavelet decomposition (DWT), quaternion singular value decomposition (QSVD) of the cover picture, and the application of octonionic transforms to concealed images are the main components of our approach. Experimental results demonstrate high-fidelity image reconstruction, with PSNR values up to 40 dB, SSIM scores reaching 0.9900, and strong robustness against various attacks. In particular, the system achieves NC ≥ 0.98 even under geometric transformations such as rotation and scaling, thanks to an integrated geometric correction module based on the Arithmetic Optimization Algorithm (AOA). The FPGA implementation ensures low-latency integrity verification, making the framework suitable for embedded healthcare environments. The proposed solution shows strong potential for protecting sensitive diagnostic data in medical systems, combining mathematical rigor with hardware-level performance. © 2025

关键词： wavelet decomposition

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wavelet-based Filtering of Noisy images by Amplification of Low-Frequency Components in High-Frequency Subbands

Wavelet-based Filtering of Noisy Images by Amplification of ...

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Digital signal processing and its applications (DSPA), International Conference on

作者： Y. S. Bekhtin V. T. Trinh Department of Automatics and Information Technologies in Control Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper describes a new method of noisy image restoration based on amplification of low-frequency components in high-frequency subbands, or details of fast wavelet transform (FWT). It makes a difference with respect to well-known wavelet filtering methods which are typically based on soft thresholding of wavelet coefficients belonging to high-frequency subbands of a noisy image. At the same time, the low-frequency component, or approximation can be used to extract the low-frequency components corresponding the details. It allows modifying the details of the FWT by adding the extracted low-frequency components that leads to increasing the signal-to-noise ratios in subbands. The paper contains the experimental results of modeling proving the effectiveness of the suggested method comparing to some widely used filtering methods, too. The results of modeling have shown that the proposed method allows improving quality of restored image by increasing both the signal-to-noise ratio and significantly reducing the number of ringing artifacts.

关键词： Wiener filters Filtering image edge detection Digital signal processing image restoration Noise measurement signal to noise ratio wavelet coefficients

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wavelet Analysis of Cardiograms in EDF Format

Wavelet Analysis of Cardiograms in EDF Format

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Digital signal processing and its applications (DSPA), International Conference on

作者： Sinan V. Kurbanov Denis A. Andrikov Department of Mechanics and Control Processes Peoples' Friendship University of Russia (PFUR) Moscow Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The correlation of the wavelet shape and the characteristic ECG section has been confirmed, and wavelets for the identification of P-, R-, and T waves have been experimentally established. An algorithm for identifying R waves in an ECG has been developed and its operability has been verified. Using the algorithm developed, a graph of the dynamics of the heartbeat period is plotted as a function of time (period number). To identify the P and T waves, the wavelet image of the real ECG is constructed, and the presence of distortion of the shape of this image due to the influence of QRS complex and neighboring waves is established. Computer removal (filtering) of QRS complexes from the ECG is carried out, wavelet image of the remaining part is calculated. The possibility of determining the positions of the maximum P- and T-waves has been established from the wavelet image of the filtered ECG. The theoretical and practical value of this study consists in a new direction of wavelet analysis of cardiac signals, by successively applying several wavelets of a special form, to identify characteristic sections of the ECG in order to improve diagnostics. The proposed method also assumes intermediate filtering of the identified sections when moving from wavelet to wavelet. The development was carried out within the framework of computer generation of arrays of digital functions of the state of the heart, suitable for training artificial intelligence systems, and diagnostics using such systems. The practical results obtained can be applied in the development of a digital expert diagnostic system or a specific technical device.

关键词： Training Correlation Shape Heart beat Filtering Heuristic algorithms signal processing algorithms Electrocardiography wavelet analysis Distortion

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Parametric Monogenic Linear Canonical wavelet Transform

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Circuits, Systems, and signal processing 2025年 1-22页

作者： Chen, Jian-Yi Li, Bing-Zhao School of Mathematics and Statistics Beijing Institute of Technology Beijing 100081 China Beijing Key Laboratory on MCAACI Beijing Institute of Technology Beijing 100081 China

This paper begins by examining the definition and fundamental properties of the two-dimensional linear canonical wavelet transform (2-D LCWT) within the framework of linear canonical transform theory. The LCWT offers significant advantages in handling multi-scale and multi-directional signals. Building on this, a novel model is proposed based on the parametric Riesz transform and parametric monogenic signal, introducing a parametric monogenic linear canonical wavelet along with its associated transform, referred to as PMLW. Through parametric embedding within the monogenic linear canonical wavelet framework, the proposed transform achieves enhanced flexibility and robustness, facilitating more efficient analysis of intricate features in complex signals. This approach leverages 2-D analytical signal theory to incorporate phase information with directional characteristics, thereby preserving rich directional details in multi-scale analysis. Furthermore, the potential applications of PMLW in image denoising tasks are explored, demonstrating its effectiveness in preserving structural details while suppressing noise. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Analytic signal Analytic wavelet transform Linear canonical transform Monogenic signal Riesz transform

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An Improved Digital signal processing for signal Enhancement and Interference Mitigation

An Improved Digital Signal Processing for Signal Enhancement...

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Automation and Computation (AUTOCOM), International Conference on

作者： Intekhab Alam Paramjit Baxi Barnali Sahoo Mohan Garg Roopashree R Thaj Mary Delsy T Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Sciences Chemistry and Biochemistry JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Digital signal processing has become a fundamental tool in signal processing applications, such as speech and image processing, due to its ability to manipulate and examine signals in a digital form skillfully. A primary challenge in signal processing involves the presence of unwanted noise and interference, which can negatively impact the precision and quality of the processed signal. The proposed advanced DSP approach aims to improve signal enhancement and interference mitigation techniques using sophisticated algorithms and methods. The proposed state-of-the-art DSP approach includes noise reduction algorithms, such as adaptive filtering and spectral subtraction, to eliminate unwanted noise from the signal. Additionally, cutting-edge signal processing techniques, such as wavelet transforms and time-frequency analysis, are used for signal enhancement and demising. The proposed approach employs adaptive equalization techniques to mitigate interference from other signals and substantially improve the overall signal quality. The enhanced DSP approach is evaluated through simulation and real-world experiments, demonstrating its effectiveness in improving signal quality and reducing interference considerably. The proposed approach has the potential to significantly improve the accuracy and reliability of various signal processing applications considerably, making it a valuable tool in fields such as telecommunications, audio and video processing, and medical signal analysis.

关键词： Wireless communication wavelet transforms Time-frequency analysis Accuracy Prevention and mitigation signal processing algorithms Interference Digital signal processing wavelet analysis Telecommunications

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Empirical wavelet Frames

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ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS 2025年第0期

作者： Gilles, Jerome Castro, Richard San Diego State Univ Dept Math & Stat 5500 Campanile Dr San Diego CA 92182 USA

Due to their adaptive nature, empirical wavelets (EWs) had several successes in many fields from engineering, science, medical signal/image processing. Recently, a general theoretical framework has been developed in the one-dimensional case, showing the possibility to build EWs from any classic mother wavelets. Given extensive literature both in theory and applications of classic wavelet frames, it is legitimate to ask about the feasibility of building EW frames. We address this question in this paper. We prove several results which provide conditions on the existence of EW frames taking into account the above-mentioned adaptability.

关键词： Empirical wavelets frames adaptive time-frequency analysis

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A Speech Enhancement Algorithm Combining wavelet Transform and Adaptive Filters

A Speech Enhancement Algorithm Combining Wavelet Transform a...

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International image processing, applications and Systems Conference (IPAS)

作者： Aayam Shrestha Seyed Ghorshi Marjan Joorabchi Issa Panahi Fereshteh Fakhar Firouzeh Department of Electrical and Computer Engineering The University of Texas at Tyler Texas USA School of Science and Engineering Sharif University of Technology Iran Department of Electrical and Computer Engineering The University of Texas at Dallas Texas USA

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Noise as an unwanted interference can significantly degrade speech signals, especially those recorded by many microphones. This interference is modeled as additive noise that originates from a range of sources including White Gaussian Noise (WGN), babble, crowd, large city, and traffic noises. These disturbances can alter the characteristics of speech signals reducing both their quality and intelligibility. This paper introduces a novel approach designed to reduce noise and enhance the quality and intelligibility of speech signals. The proposed method combines wavelet Transform with Adaptive Filters, specifically the Wiener filter and RLS filter. The evaluation process involves testing noisy speech signals under realistic conditions with different signal-to-noise ratios (SNRs) and different types of additive noise. The objective measure is used for evaluation, including the perceptual evaluation of speech quality (PESQ). Results show that combining Wiener or RLS filtering with wavelet Transform significantly improves noise reduction, outperforming the use of wavelet Transform alone.

关键词： wavelet transforms Additive noise Wiener filters Filtering Noise Urban areas Adaptive filters Interference Speech enhancement wavelet analysis

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Comparison of Widely-used image Restoration Methods for Additive and Multiplicative Noises

Comparison of Widely-used Image Restoration Methods for Addi...

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Digital signal processing and its applications (DSPA), International Conference on

作者： Mohammad Zedan Yury S. Bekhtin dept. Diagnostic Information Technologies National Research University “MPEI” Moscow Russian Federation dept. Automatics and Information Technologies in Control Ryazan State Radio Engieneering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper evaluates and compares the performance of various image denoising techniques, including wavelet transform, Wiener filtering, non-local means (NLM), denoising autoencoders (DAEs), and feedforward autoencoders. There are cases of additive and multiplicative noises considered where the Gaussian distribution with zero mean stands for the first case and an exponential distribution with unity mean describes the second case (speckle). The experiments have been conducted on the given dataset which contained both still test images and synthetic aperture radar (SAR) images with varying noise levels to analyze the effectiveness of these denoising approaches. The performance of each method is assessed using key image quality metrics: Peak signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Squared Error (MSE), and Normalized Absolute Error (NAK). The results demonstrate that denoising autoencoders DAEs provide superior performance in terms of structural preservation and noise reduction, particularly in low-noise conditions, while Wiener filtering proves to be computationally efficient and robust under high-noise conditions. These findings offer insights into the selection of effective denoising techniques for noisy images based on specific noise characteristics and application requirements.

关键词： wavelet transforms Wiener filters Additives PSNR Autoencoders Speckle Radar polarimetry Computational efficiency image restoration Noise level

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An Improved Digital signal processing for signal Enhancement and Interference Mitigation

An Improved Digital Signal Processing for Signal Enhancement...

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3rd IEEE International Conference on Automation and Computation, AUTOCOM 2025

作者： Alam, Intekhab Baxi, Paramjit Sahoo, Barnali Garg, Mohan Roopashree, R. Thaj Mary Delsy, T. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542375

关键词： image enhancement

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