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A New Design and VLSI Implementation of Symmetric Daubechies Wavelet Filter Bank for image processing applications

CIRCUITS SYSTEMS AND signal processing 2025年第5期44卷 3625-3640页

作者： Samantaray, Aswini K. Rahulkar, Amol D. Sahoo, Satyajeet Gorre, Pradeep Manipal Inst Technol Bengaluru Manipal Inst Higher Educ Dept ECE Manipal India Natl Inst Technol Dept EEE Veroda Goa India Vignans Fdn Sci Technol & Res Dept ECE Guntur India

Due to the irrational coefficients, the orthogonal wavelet filter banks (FBs) need a lot of resources when implemented on hardware. As a result, there is a decrease in operating speed, a significant memory requirement, and an increase in power consumption. This paper proposes an orthogonal low complex symmetric Daubechies-2 (4-tap) wavelet filter bank (FB) to address these problems. This is accomplished by obtaining dyadic filter coefficients and making the suggested FB symmetric by marginally modifying the perfect reconstruction (PR) criterion. By using fewer adders and shifters, the suggested wavelet FB achieves a significant reduction in dynamic power consumption without the need for multipliers. This is confirmed by implementing the suggested wavelet FB on the Zedboard ZYNQ-7000 AP-SoC (Zynq FPGA from xilinx) field programmable gate array (FPGA). The suitability of the suggested FB is tested in medical image retrieval and image compression applications. Results from simulations demonstrate that, when compared to state-of-the-art techniques, the suggested wavelet FB performs better in terms of retrieval accuracy (ARP, ARR) for medical image retrieval and PSNR for image compression on the benchmark image datasets.

关键词： Orthogonal wavelets Perfect reconstruction Field programmable gate array image compression image retrieval

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Robust Multilayer Matrix Factorization for Blind Hyperspectral image Unmixing 16

Robust Multilayer Matrix Factorization for Blind Hyperspectr...

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16th International conference on signal processing Systems, ICSPS 2024

作者： Yang, Gang Southwest China Institute of Electronic Technology Chengdu China

ISBN: (纸本)9781510689251

Hyperspectral image unmixing estimates a collection of constituent materials (called endmembers) and their corresponding proportions (called abundances), which is a critical preprocessing step in many remote sensing applications. In this paper, we propose a novel robust multilayer matrix factorization (RMLMF) approach for hyperspectral image unmixing. Firstly, instead of sampling all observed pixels, the endmembers are modeled as a linear combination of candidate endmembers to reduce the redundant spectra and alleviate heavy computational cost. Secondly, to explore the hidden information, the shallow decomposition is extended into multilayer structure. Furthermore, considering that hyperspectral images (HSIs) still suffer from a variety of noises, L2,1-norm is employed to measure the reconstruction error of the multilayer structure. Experimental results on both synthetic and real data sets demonstrate the superiority of the proposed RMLMF over many state-of-the-art algorithms. © 2025 SPIE.

关键词： Matrix factorization

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Optimized image processing on FPGAs: Comparative Analysis of Adder Architectures for image Smoothing applications

Optimized Image Processing on FPGAs: Comparative Analysis of...

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2025 IEEE International Students' conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Varun, G. Abhinav Chaitanya, R. Jagadeesh, J. Sm, Sakthivel School of Electronics Engineering Chennai India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529833

image smoothening is a highly utilized operation in digital image processing focused on reducing the impact of noise. In field programmable gate arrays (FPGA) based implementation, the working of the image smoothening process depends on the arithmetic components, particularly the adder structures. Modifying the underlying adder structures would have a significant impact on the efficiency of image processing. This paper presents a comparative analysis of four advanced adder architectures - like optimized lower part constant or adder (OLOCA), hardware optimized approximate adder with normal error distribution (HOAANED), brent-kung adder, and kogge-stone adder - against the conventional ripple carry adder (RCA). Different adder's impact is evaluated based on delay, power consumption, resource utilization, and peak signal-to-noise ratio (PSNR). Our findings demonstrate how selecting an optimal adder can impact the performance of FPGA-based image-smoothening applications. © 2025 IEEE.

关键词： image analysis

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signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic processing for ML-Driven applications

Signal-Centric Remote Sensing via Alternative Preprocessing ...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Luna, Logan Jansen-Sánchez, Sirio Demirkiran, Ilteris Ghelarducci, Leo Embry-Riddle Aeronautical University Daytona Beach United States

ISBN: (纸本)9798331504847

The dominant method of processing sonar data is using image-based representations, requiring the preprocessing of image data on autonomous systems. We propose an alternative data processing method for remote sensing applications via the use of data in Comma-Seperated Value format. Experimentation on our alternative approach shows a reduction of processing time by 91.18%, an improvement in accurate object detection by Machine Learning, and an increase in SNR (signal-to-noise ratio), PSNR (Peak signal-to-noise ratio), and other evaluation metrics. © 2025 IEEE.

关键词： Data curation

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Research on image optimization of graphic design based on 3D laser vision technology 2

Research on image optimization of graphic design based on 3D...

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2nd International conference on Big Data, Computational Intelligence, and applications, BDCIA 2024

作者： Yang, Dianqing Liu, Renjing Visual Design College Keimyung University Dalseo-gu Daegu704-701 Korea Republic of

ISBN: (纸本)9781510689053

To prevent image distortion, this paper explores methods for enhancing and optimizing graphic design images using 3D laser vision technology. The process involves collecting graphic design image data, mapping 3D laser information onto the surface of the image to form an information map, and utilizing this data for locally weighted complexity processing. A histogram of the graphic design image is constructed, followed by scanning and grayscale transformation to eliminate noise. The image histogram is then segmented using a block-based local enhancement method to achieve the optimization and enhancement of the graphic design image. Experimental results show that under different noise standard deviations, the average peak signal-to-noise ratio (PSNR) of the proposed method is 36.62 dB, and the average structural similarity index (SSIM) is 0.9526. This method effectively reduces noise and enhances the visual quality of graphic design images, improving the ability of the human eye to discriminate information in these images. © 2025 SPIE.

关键词： image enhancement

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RDM: A Light Field Super-Resolution Model Improved with Retinex Decomposition 16

RDM: A Light Field Super-Resolution Model Improved with Reti...

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16th International conference on signal processing Systems, ICSPS 2024

作者： Lyu, Wenqi Ke, Wei Sheng, Hao Ma, xiao Liu, Lixue Faculty of Applied Sciences Macao Polytechnic University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781510689251

Light field cameras hold significant value in applications such as depth estimation, 3D video acquisition, and image super-resolution. Compared to traditional single-image super-resolution methods, light field images can capture object information from multiple spatial and angular perspectives, which is more conducive to capturing detail information. However, current advanced light field super-resolution models still exhibit issues like blurriness, jaggedness, and dimness in 4x light field super-resolution. To address this, we propose a novel light field super-resolution framework that utilizes the Retinex decomposition concept to solve common problems such as ghosting and overlap, thereby improving image quality. By decomposing the light field image into illumination and reflection components and processing them separately, our model significantly enhances detail preservation and color consistency. Experimental results on multiple datasets demonstrate that our model exhibits outstanding performance, both subjectively and objectively, highlighting the effectiveness of this framework and its broad application potential in the field of computational imaging. © 2025 SPIE.

关键词： image acquisition

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An optimized scheme of computer-generated hologram compression with convolutional neural networks and genetic algorithm 2

An optimized scheme of computer-generated hologram compressi...

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2nd International conference on Optical Communication and Optical Information processing, OCOIP 2024

作者： Yao, Yuxuan Yang, Guanglin Laboratory of Signal and Information Processing School of Electronics Peking University Beijing100871 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

Holography is pivotal in various applications ranging from microscopy to data storage. However, the practical implementation of holography often necessitates compression, which inevitably degrades the quality of the reconstructed images. Addressing this challenge, a scheme of computer-generated hologram compression with convolutional neural networks optimized is proposed. In this scheme, our research investigates the potential of genetic algorithm, a class of evolutionary algorithms inspired by natural selection, to optimize the initial weights of the network. Experimental results show that the scheme is feasible. © 2025 SPIE.

关键词： Convolutional neural networks

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An image encryption algorithm based on non-degenerate chaos and dynamic Bi-directional permutation 16

An image encryption algorithm based on non-degenerate chaos ...

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16th International conference on signal processing Systems, ICSPS 2024

作者： Liao, Yunlong xu, Qingyang Zhang, Qiyuan xing, Zheng Yuan, xiaochen Faculty of Applied Sciences Macao Polytechnic University China

ISBN: (纸本)9781510689251

In the wake of the accelerated advancement of Internet of Things(IoT) technology, a significant volume of multimedia information is emerging as the dominant component of IoT applications. However, this information also led to big security risks. Therefore, a secure and reliable image encryption scheme based on non-degenerate hyper chaos and dynamic bidirectional permutation is proposed for the characteristic of digital images which the primary information carrier in the IoT communication environment. The scheme uses non-degenerate discrete chaos to generate pseudo-random sequences and applies them to the encryption process involving image confusion, dynamic permutation, and dynamic diffusion. Through theoretical analysis and experimental verification, the algorithm exhibits high sensitivity to both the plaintext images and the ciphertext images. Concurrently, it can effectively resist common noise attacks and cryptographic attacks. In conclusion, the proposed scheme offers superior encryption capabilities and stands as a secure solution, compatible with a diverse range of IoT environments. © 2025 SPIE.

关键词： Chaos theory

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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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IRT-diffusion: combined denoising diffusion probabilistic models with thermal signal processing methods for automated defect detection in composites using infrared thermography

IRT-diffusion: combined denoising diffusion probabilistic mo...

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2024 International conference on Optical and Photonic Engineering, icOPEN 2024

作者： Wei, Yanjie Zhang, Yuhang xiao, Yao Gu, xiaohui State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China Department of Engineering Mechanics Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

Infrared thermography (IRT) is a reliable method for detecting defects in composites with advantages of full field, non-contact, easy operation and good visualization. Nevertheless, interpretation by experts is required to distinguish between defective and sound regions in the practical evaluation of defects, which limits the industrial applications of infrared thermography. In this study, a denoising diffusion probabilistic model (DDPM) framework named IRT-Diffusion is proposed to automatically segment defective regions in thermal images. IRT-Diffusion can reconstruct a defect segmentation image from a noisy image with standard Gaussian distribution by iteratively performing multiple denoising operations. Detection results from various traditional thermal signal processing methods are employed as input for the conditional noise predictor of IRT-Diffusion to generate more accurate defect segmentation results. The core innovation of this study is that the state-of-the-art generative model is first introduced and designed for defect identification in composites using infrared thermography. To assess the performance of IRT-Diffusion, experiments were conducted on several composites panels and compared with conditional variational autoencoder (CVAE) and conditional generative adversarial network (CGAN). The results demonstrate that the proposed method achieves superior quantitative metrics and effectively extracts defective regions. © 2025 SPIE.

关键词： image segmentation

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