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FoNet: Focused Network for Single image Deraining

CIRCUITS SYSTEMS AND signal processing 2025年第6期44卷 4198-4223页

作者： Gumma, Sambasiva Rao Chintakindi, Balaram Murthy VIT AP Univ Sch Comp Sci & Engn Amaravati Andhra Pradesh India

The task of single-image deraining focuses on generating clear images from rainy ones, a crucial challenge with wide-ranging applications. Although Transformer models have achieved notable success in this field, their quadratic computational complexity hinders practical use. To address this, we propose a lightweight and efficient solution called the Focused Network (FoNet), which is designed to handle varying degrees of degradation across different image regions. FoNet incorporates a Binary Domain Selection Mechanism to emphasize critical features such as edges and highly degraded areas, while Multi-scale Residual Units are used to improve both efficiency and performance. Built on a U-net architecture, the network demonstrates a PSNR improvement of + 0.62 dB over state-of-the-art methods, processes images within 9 ms, and requires only 3.74 million parameters. These findings highlight the practicality and effectiveness of our approach in advancing single-image deraining.

关键词： FocusedNet Single image deraining Binary domain selection mechanism Multi-scale residual unit

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Convolution based fractional Wigner distribution and ambiguity function: theory and applications

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JOURNAL OF PSEUDO-DIFFERENTIAL OPERATORS AND applications 2024年第4期15卷 1-29页

作者： Dar, Aamir H. Zayed, Mohra Bhat, M. Younus Shanghai Inst Math & Interdisciplinary Sci SIMIS Shanghai 200433 Peoples R China King Khalid Univ Coll Sci Math Dept Abha 61413 Saudi Arabia Islamic Univ Sci & Technol Dept Math Sci Awantipora 192122 Kashmir India

There has been a significant increase in the use of the Fractional Fourier transform (FrFT) in recent years due to its numerous applications in signal and image processing, among other fields. At the same time, the applications of Wigner distributions (WD) and ambiguity functions (AF) in signal analysis and image processing cannot be excluded. This paper investigates the convolution-based WD and AF associated with the Fractional Fourier transform (CFrWD/CFrAF). Firstly, we propose the definition of the CFrWD and CFrAF, and then relations with other classical time-frequency representations of the newly defined CFrWD and CFrAF are investigated. Furthermore, some essential properties, including conjugate-symmetry, nonlinearity, shifting, scaling, marginal, Moyal's formula, and convolution, are also examined in detail. Finally, to demonstrate the benefit of the theory, applications of CFrWD and CFrAF for detecting LFM signals are also carried out with the aid of simulations.

关键词： Fractional Fourier transform Wigner distribution Moyal's formula Convolution LFM signal

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Hessian-based weighted guided image filtering

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signal image AND VIDEO processing 2025年第1期19卷 1-14页

作者： Wu, Jiaxin xie, Shoulie Cao, Wei Wu, Shiqian Wuhan Univ Sci & Technol Inst Robot & Intelligent Syst Sch Informat Sci & Engn Wuhan 430081 Peoples R China Inst Infocomm Res Singapore 138632 Singapore Rehabil Univ Sch Rehabil Sci & Engn Qingdao 266000 Peoples R China Henan Acad Sci Rehabil Univ Inst Adv Displays & Imaging Zhengzhou 450046 Peoples R China

Guided image filtering (GIF) is a popular edge-preserving smoothing technique, and the regularization parameter selection plays an important role in the performance of GIF. In this paper, we propose a new guided image filter based on Hessian matrix which consists of the second-order derivatives of an image. More specifically, a new structural measurement index is introduced by using the eigenvalues of the Hessian matrix first, which can distinguish the texture and flat regions of the image. Then the regularization parameter is adjusted based on this Hessian-based second-order structure measurement index, that is, a large regularization parameter is selected to improve the smoothness of the flat regions, while a small regularization parameter is set for the texture regions to preserve the image structure such as edges and corners. To further improve the quality of the filtered images, we also introduce a weighted averaging technique to the linear filter coefficients based on local variance. Experimental results show that the proposed Hessian-based weighted guided image filtering method outperforms the state-of-the-art approaches in image processing applications such as edge-preserving denoising, detail enhancement, dehazing, HDR compression, artifact removal, and scale representation.

关键词： Guided image filtering Content-aware filtering Edge-preserving smoothing Detail enhancement Denoising Dehazing HDR compression Artifact removal Scale representation

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Harmonic analysis on directed graphs and applications: From Fourier analysis to wavelets

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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS 2023年 62卷 390-440页

作者： Sevi, Harry Rilling, Gabriel Borgnat, Pierre CEA LIST Lab Sci Donnees & Decis F-91400 Gif Sur Yvette France Univ Lyon Ens Lyon CNRS Lab Phys F-69342 Lyon France Univ Paris Saclay Ctr Borelli CNRS ENS Saclay France

We introduce a novel harmonic analysis for functions defined on the vertices of a strongly connected directed graph (digraph) of which the random walk operator is the cornerstone. As a first step, we consider the set of eigenvectors of the random walk operator as a non-orthogonal Fourier-type basis for functions over digraphs. We find a frequency interpretation by linking the variation of the eigenvectors of the random walk operator obtained from their Dirichlet energy to the real part of their associated eigenvalues. From this Fourier basis, we can proceed further and build multi-scale analyses on digraphs. We propose both a redundant wavelet transform and a decimated wavelet transform as an extension of spectral graph wavelets and diffusion wavelets framework respectively for digraphs. The development of our harmonic analysis on digraphs thus leads us to consider both semi-supervised learning problems and signal modeling problems on graphs applied to digraphs highlighting the efficiency of our framework. (c) 2022 Elsevier Inc. All rights reserved.

关键词： Harmonic analysis Graph signal processing Fourier analysis wavelets Directed graphs Random walks Semi-supervised learning

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Digital signal processing

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Digital signal processing

作者： Kutluyil Dogancay

出版社：ACADEMIC PRESS INC ELSEVIER SCIENCE

Digital signal processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal . The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: big data machine learning internet of things information security systems biology and computational biology financial time series analysis autonomous vehicles quantum computing neuromorphic engineering human-computer interaction and intelligent user interfaces environmental signal processing geophysical signal processing including seismic signal processing chemioinformatics and bioinformatics audio, visual and performance arts disaster management and prevention renewable energy We welcome also submissions in the fundamental areas such as information theory and on mathematical topics with potential applications in signal processing such as functional analysis, stochastic calculus, game theory and group theory. Papers in the classical application areas of signal processing such as telecommunications, speech, image and video processing are welcome only if they contain novel research into methodology. Purely application oriented articles in these areas should be submitted to the relevant dedicated journals. Digital signal processing: A Review Journal also aims to publish quality review articles in addition to occasional focus issues with special emphasis on emerging topics. Discussion articles in which several leading researchers discuss the future of a specific research area are also welcome. For details of the journal's speeds and other metrics, plea

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Optimized Algorithms and Hardware Implementation of Median Filter for image processing

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CIRCUITS SYSTEMS AND signal processing 2023年第9期42卷 5545-5558页

作者： Draz, H. H. Elashker, N. E. Mahmoud, Mervat M. A. Elect Res Inst Microelect Dept Cairo Egypt Cairo Univ Fac Engn Commun & Elect Dept Cairo Egypt British Univ Egypt Elect Engn Dept Cairo Egypt

image processing algorithms are essential for clarifying the image and improving the ability to recognize distinct characteristics of the image. The field of digital image processing is widespread in several research and technology applications. In many of these applications, the existence of impulsive noise in the obtained images is one of the most frequent problems. The median filter is a strong method to remove the impulsive noise;it effectively eliminates salt and pepper noise from the image. The main target of this paper is to investigate efficient median filter units to be connected to a general-purpose processor (GPP) for FPGA-based embedded systems. The paper exposes three novel techniques, two of them specially for median filtering techniques and the third one is used to get the maximum number of any 9 elements array. The proposed algorithms are inspired by the Median Of Median (MOM) algorithm. The first two techniques are tested for filtering 3 x 3 image windows and optimized for producing the expected result in high accuracy, short time, and reduced number of comparisons. The last technique is tested for a 9 elements array for extracting the maximum number in same high efficiency manner. Furthermore, the three proposed techniques are implemented leveraging the advantage of the parallel processing and the FPGA flexible resources to satisfy the real-time processing constraints. A comparison between the first two proposed filtering units and their counterparts in the literature is included. The comparison reveals the superiority of the first technique in terms of accuracy with fewer comparators than previously published techniques. Besides, the paper illustrates how the concept beyond the proposed techniques can be used to perform the maximum pooling for convolution neural networks.

关键词： Embedded systems FPGA image de-noising Median filter Median of medians

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Precise Hardware Implementation of Directional Median Filter with Energy-Saving

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CIRCUITS SYSTEMS AND signal processing 2025年 1-22页

作者： Abd El-Wahab, Shaymaa Mahmoud, Mervat M. A. Shawky, Heba Shokair, Mona Elect Res Inst Microelect Dept Cairo Egypt Menoufia Univ Dept Elect & Elect Engn Menoufia Egypt October 6 Univ Fac Engn Dept Elect Engn Giza Egypt

The efficacy of the Directional Median Filter (DMF) in restoring images corrupted by impulse noise has been demonstrated in various image processing applications. Conversely, its complex algorithm presents challenges to its hardware implementation. This paper discusses the 5x5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$5 \times 5$$\end{document} window DMF methodology, emphasizing improvements in image edge pixels preservation. This modification aims to address the issue of pixel noise at the edge. Furthermore, we suggest a clock-gated hardware implementation of the modified DMF. We implement the design using NanGate 45 nm Technology and Virtex UltraScale FPGA. To ensure the validity of our design, we developed a software model of the suggested DMF in MATLAB, which was used to verify the algorithm's functionality and performance against noise-corrupted images. Despite the hardware implementation involving an approximation for computationally intensive operations such as division and square root, the accuracy of the hardware results remains comparable to state-of-the-art filtration methods. The suggested hardware implementation is highly efficient in terms of power and energy consumption. In comparison to the state-of-the-art, the power consumption is reduced by approximately 45% to 60%, while energy consumption is decreased by 30-50%. Consequently, the design is well-suited for low-energy applications.

关键词： Application specific integrated circuit (ASIC) Clock gating Directional median filter Field programmable gate arrays (FPGA) image denoising

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Mitigation of DMM-induced stripe patterns in synchrotron x-ray radiography through dynamic tilting

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JOURNAL OF SYNCHROTRON RADIATION 2024年第6期31卷 1551-1560页

作者： Eddah, Mustapha Markoetter, Henning Mieller, Bjorn Sintschuk, Michael Beckmann, Jorg Bruno, Giovanni Bundesanstalt Mat Forsch & Prufung BAM Div Xray Imaging 8 5 Eichen 87 D-12205 Berlin Germany Bundesanstalt Mat Forsch & Prufung BAM Div Adv Multimat Proc 5 4 Eichen 87 D-12205 Berlin Germany

In synchrotron x-ray radiography, achieving high image resolution and an optimal signal-to-noise ratio (SNR) is crucial for the subsequent accurate image analysis. Traditional methods often struggle to balance these two parameters, especially in situ applications where rapid data acquisition is essential to capture specific dynamic processes. For quantitative image data analysis, using monochromatic x-rays is essential. A double multilayer monochromator (DMM) is successfully used for this aim at the BAMline, BESSY II (Helmholtz Zentrum Berlin, Germany). However, such DMMs are prone to producing an unstable horizontal stripe pattern. Such an unstable pattern renders proper signal normalization difficult and thereby causes a reduction of the SNR. We introduce a novel approach to enhance SNR while preserving resolution: dynamic tilting of the DMM. By adjusting the orientation of the DMM during the acquisition of radiographic projections, we optimize the x-ray imaging quality, thereby enhancing the SNR. The corresponding shift of the projection during this movement is corrected in post-processing. The latter correction allows a good resolution to be preserved. This dynamic tilting technique enables the homogenization of the beam profile and thereby effectively reduces noise while maintaining high resolution. We demonstrate that data captured using this proposed technique can be seamlessly integrated into the existing radiographic data workflow, as it does not need hardware modifications to classical x-ray imaging beamline setups. This facilitates further image analysis and processing using established methods.

关键词： double multilayer monochromators synchrotron x-ray imaging signal normalization BAMline dynamic tilting

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High-Speed and Area-Efficient Serial IMPLY-Based Approximate Subtractor and Comparator for image processing and Neural Networks

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IEEE TRANSACTIONS ON NANOTECHNOLOGY 2024年 23卷 748-757页

作者： Kaushik, Nandit Srinivasu, B. Indian Inst Technol Mandi Sch Comp & Elect Engn Mandi 175005 India

In-Memory-Computing (IMC) through memristive architectures has recently gained traction owing to their capacity to perform logic operations within a crossbar, optimizing both area and speed constraints. This paper introduces two approximate serial IMPLY-based subtractor designs, denoted as Serial IMPLY-based Approximate Subtractor Design-1 (SIASD-1), Serial IMPLY-based Approximate Subtractor Design-2 (SIASD-2), with potential applications in image processing and deep neural networks. The proposed designs are implemented in MAGIC topology for comparison, named as Serial MAGIC-based Approximate Subtractor Design-1 (SMASD-1) and Serial MAGIC-based Approximate Subtractor Design-2 (SMASD-2). Moreover, these proposed subtractor designs are extended to design magnitude comparators. IMPLY-based approximate designs improve the overall latency up to 1.67x with energy savings in the range of 17.4% to 40.3% while occupying the same number of memristors for SIASD-1 and an increase of 3 to 5 memristors for SIASD-2, compared to the best existing exact 8-bit serial IMPLY subtractor. SMASD-1 and SMASD-2 improve the latency up to 1.43x, and energy efficiency are up by 77.6% compared to other MAGIC-based exact designs. Additionally, as comparators, the SIASD-1 and SIASD-2 are up to 4.93x faster with energy reduction up to 79.7% compared to their IMPLY-based equivalents. Similarly, the SMASD-1 and SMASD-2 reduce the latency up to 62% with area savings of 77%, compared to MAGIC-based equivalent designs. Furthermore, the proposed subtractor designs undergo analysis in an image processing application called Motion Detection, while the comparators are evaluated in Max Pooling operations. With Peak signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) serving as assessment metrics, the proposed designs consistently demonstrate acceptable PSNR and SSIM values, affirming their suitability for these applications.

关键词： Memristors Circuits Logic image processing Voltage Topology Neural networks Adders Switches Network topology IMPLY MAGIC subtractor memristor adder in-memory computing comparator

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Comparison of Multi-Modal Large Language Models with Deep Learning Models for Medical image Classification 8

Comparison of Multi-Modal Large Language Models with Deep Le...

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IEEE 8th International Conference on signal and image processing applications (IEEE ICSIPA)

作者： Than, Joel Chia Ming Vong, Wan Tze Yong, Kelvin Sheng Chek Swinburne Univ Technol Sch Informat Comp & Technol Sarawak Campus Kuching Malaysia

ISBN: (纸本)9798350352368

In recent years, the advancement of large language models (LLMs) such as GPT-4 and Gemini has opened new avenues for artificial intelligence applications in various domains, including medical image classification. This study aims to compare the performance of multi-modal LLMs with state-of-the-art deep learning networks in classifying tumour and non-tumour images. The performance of four multi-modal LLMs and four conventional deep learning methods were evaluated using several performance measures. The results demonstrate the strengths and limitations of both approaches, providing insights into their applicability and potential integration in clinical practice. Gemini 1.5 Pro performs the best out of the eight models evaluated. This comparison underscores the evolving role of AI in enhancing diagnostic accuracy and supporting medical professionals in disease detection especially when training data is scarce.

关键词： LLM multi-modal deep learning classification image

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