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Investigating the Efficiency of digital image Sampling in Serial image processing

Investigating the Efficiency of Digital Image Sampling in Se...

Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS), IEEE International Conference on

作者： Saravanan V M Rajat Saini P. Vijayaraghavan Swati B. Patil Savita Prabha Vaishali Singh Department of Animation and Virtual Reality Jain (Deemed to be University) Bangalore Karnataka India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab Department of Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Information Technology Vishwakarma Institute of Information Technology Pune India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350329773

ISBN: (纸本)9798350329780

The reason of this look at is to observe the efficiency of virtual photograph sampling in serial image processing. This investigation covers the impact of sampling strategies on image great, the efficiency of facts compression, and the computational complexity of algorithms used in serial photograph processing. The studies is carried out the usage of numerous open source libraries and methods that are suitable for studying digital photos and the results of making use of virtual photograph sampling strategies. Several experiments are designed to degree the impact of different sampling techniques on serial photograph processing. including easy pixel sampling, down sampling, and advanced techniques including adaptive non-uniform sampling and virtual filtering. Additionally, the appropriateness of the contemporary state of current sampling algorithms is assessed. The outcomes of this look at are anticipated to provide beneficial insights for designers of serial image processing.algorithms and to pick out ability areas for improvement. Moreover, this paintings is expected to provide hints for optimizing the effectiveness of virtual image sampling techniques in terms of photograph quality, computational complexity, and statistics compression.

关键词： Visualization image coding Filtering digital images image sampling Libraries Computational complexity

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Research of digital image processing.Technology of Photoelectric Theodolite’s Target Based on MATLAB

Research of Digital Image Processing Technology of Photoelec...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Ke Li Lijian Zhao Ruxiang Xu Haiyuan Zhou Xinming Liu Fanyuan Qian Xiaodong Sun Marine Department of Satellite Tracing and Metering Jiangyin China

digital image processing.is a technique to digitized image data,which is also called computer image processing. Modern technology keeps digital image processing.evolving and expands the application scope. Because of the complexity of the sea scene, as well as the the characteristics of the photoelectric theodolite, the background of uneven homogeneity can be occured in the measured images over the time, and various kinds of clouds and other complex backgrounds may appear a because of the changing weather. How to suppress the diverse backgrounds, enhance the contrast and improve the target extraction ability are the key to successfully capturing the tracking target. This paper takes the processing.operation of edge detection and pseudo-color processing. Meanwhile, an improved K-means clustering method is proposed; different kinds of clusters were selected for different kinds of images and realized the rapid and effective image segmentation. The clear edge and detail of image can be realized after the abovementioned operations. In this paper, the processing.algorithm of the theodolite image has advantages and disadvantages,the corresponding algorithm can be taken according to specific requirements in practical application, which can be technical reference for the image target recognition and feature extraction.

关键词： image segmentation Target tracking Theodolites Target recognition image edge detection digital images Clustering algorithms

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Design of a Stochastic Computing architecture for the Phansalkar Algorithm

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2024年第3期32卷 442-454页

作者： Zhang, Yongqiang Qin, Jiao Han, Jie Xie, Guangjun Hefei Univ Technol Sch Microelect Hefei 230009 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 1H9 Canada

Binarization plays a key role in image processing. Its performance directly affects the success of subsequent character segmentation and recognition. The Phansalkar algorithm performs excellent in processing.heavily degraded or poor-quality images. However, this algorithm incurs significant hardware costs. In this article, efficient stochastic computing (SC) functions and an architecture are proposed for the Phansalkar algorithm. Highly accurate stochastic elements are designed for this architecture, including a stochastic mean circuit (SMC), a stochastic unipolar subtractor (USUB), a stochastic square root circuit (SQRT), and a stochastic exponential circuit (SEXP). Simulation results show that the SC architecture using 64-bit streams for the Phansalkar algorithm provides sufficient accuracy. Physical implementation indicates the effectiveness of the proposed architecture in lowering hardware costs for this algorithm compared with the binary counterpart.

关键词： Computer architecture Hardware Costs Classification algorithms Logic gates Gray-scale Correlation image binarization Phansalkar algorithm stochastic computing (SC)

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Light-Weight Low-Latency Reconfigurable CORDIC architecture With a New Non-Power-of-2 Angle Set of Microrotations

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年

作者： Verma, Anu Das, Bishnu Prasad Indian Inst Technol IIT Roorkee Dept Elect & Commun Engn Roorkee 247667 Uttarakhand India

Trigonometric functions are widely used in various scientific and engineering applications, including digital signal processing. This article proposes a low-complexity low-latency reconfigurable CORDIC (COordinate Rotation digital Computer) algorithm that computes trigonometric functions, which is based on a novel angle set of microrotations. The CORDIC algorithm is an iterative algorithm that reduces the performance due to the high latency of computation. The proposed pipelined scale-free CORDIC algorithm computes the functions in only four iterations with an optimized angle set of microrotations with high accuracy. It can be configured in two modes with different trajectories 1) rotation-mode;and 2) vectoring-mode for circular and hyperbolic trajectories. On-board FPGA implementation of the proposed architecture consumes 34.95% less register, 48.12% less occupied slices, 19.06% less LUTs, 66.51% less slice-latency product (SLP), 59.29% less LUT-latency product (LLP), and 71.23% less register-latency product (RLP) compared to the best existing state-of-the-art CORDIC architectures. Moreover, the latency of the proposed architecture is 72.34% less than the best of existing designs. Besides, the parasitic-extracted layout simulation results of the proposed design across different word lengths are reported in TSMC 65-nm CMOS technology for the validation of the proposed architecture.

关键词： Computer architecture Accuracy Hardware Trajectory Convergence Taylor series Pipelines Complexity theory Table lookup Signal processing.algorithms Coordinate rotation digital computer (CORDIC) reconfigurable CORDIC FPGA ASIC

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A high-speed hardware accelerator for lightweight dehazing neural network based on SFA-Net

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JOURNAL OF REAL-TIME image processing 2025年第2期22卷 1-16页

作者： Chen, Zhe Du, Gaoming Li, Zhenmin Wang, Xiaolei Yin, Yongsheng Hefei Univ Technol Hefei Peoples R China

In adverse weather conditions such as haze, a large number of suspended particles are present in the atmosphere, which may interfere with the real-time and high-quality acquisition of visual images in applications such as remote sensing, monitoring, and automotive systems. Existing neural network-based algorithms require high computational power and storage, resulting in poor real-time performance. To address these issues, this paper proposes a lightweight spanning fusion attention convolutional neural network (SFA-Net), which adopts an autoencoder architecture and utilizes feature attention fusion to manipulate the interaction between Channel Attention (CA) and Pixel Attention (PA) information, and connects the feature information of the front and back convolutional layers through an adaptive mixup fusion module to train the defogging model and reconstruct clear images. In addition, a configurable and efficient hardware acceleration circuit based on the network is designed, which can be applied to different indoor and outdoor scenarios. Experimental results show that the proposed method has a good dehazing ability with only 720 parameters, and is better than the indicators of other hardware implementation algorithms in the comparison of objective data sets. In terms of hardware, compared with the brightness improved by light-dehazeNet (BILD-Net), the resource is reduced by 48%, and the processing.speed can reach a maximum frame rate of 120 frames per second, which meets the requirements of real-time processing.

关键词： CNN Dehazing Hardware accelerator FPGA image processing

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Research on image random matrix modeling and stylized rendering algorithm for painting color learning

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JOURNAL OF INTELLIGENT SYSTEMS 2025年第1期34卷

作者： Zhou, Ying Zhang, Yang Kaifeng Vocat Coll Culture & Arts Dept Foreign Language Teaching Kaifeng 475000 Henan Peoples R China Kaifeng Vocat Coll Culture & Arts Dept Arts Kaifeng 475000 Henan Peoples R China

In recent years, the widespread adoption of image capture equipment and advances in image-based computer graphics have made the extraction and application of image structure information, such as gradient fields and lines, a key focus in the field of image processing. Nowadays, most mobile devices have relatively good shooting functions, so people's demands for multimedia information processing.are becoming stronger and stronger. In this study, an importance-driven picture composition method combining various rendering styles is proposed. The importance of each pixel in the picture is estimated based on image saliency or specified by user interaction. This method combines various rendering styles such as color desaturation, line rendering, edge preserving blur and contrast enhancement, and is suitable for image, video, 3D scene and even mixed reality scene. Highlighting the importance of image structure analysis, this study explores innovative methods to enhance the visual quality of augmented reality and stylization algorithms for images and videos. By delving into various rendering techniques, such as color desaturation and line rendering, it aims to significantly improve both the aesthetic appeal and functionality of digital media across diverse platforms, thereby meeting the growing demands for advanced multimedia processing.

关键词： matrix modeling stylized rendering paint color

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A Survey on Automated Disease Diagnosis and Classification of Herbal Plants Using digital image processing

A Survey on Automated Disease Diagnosis and Classification o...

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International Conference on Information Systems and Computer Networks (ISCON)

作者： Ankit Khandelwal Aasheesh Shukla Mangal Sain Electronics & Communication Dept. GLA University Mathura India Information Engineering Dept. Dongseo University Busan Republic of Korea

This paper presents a review on automated disease detection processing. The primary issue in herbal plants is the diagnosis and stratification of its diseases. The conventional process is unpredictable and inconsistent, therefore techniques for classifying plants diseases using digital method are necessary as they speed up the identification process. This literature discusses various digital methods for classifying plant diseases. The first step is image processing.of herbal plants, which make use of traditional image processing.techniques and algorithms to categories diseases in herbal plants based on attributes like texture, color, and shape. The second step is plant categorization based on deep learning and machine learning, such as CNN, KNN, logistic regression etc. Deep learning applications mainly lessen the reliance on designs and preprocessing.techniques by joining the entire process. This review provides a basic understanding and knowledge of the current state-of-the-art researches, as well as some dynamic trends for future work.

关键词： Deep learning Plant diseases Machine learning algorithms Shape image color analysis digital images Neurons

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Investigating the Effects of image Restoration algorithms on image Quality in digital image processing

Investigating the Effects of Image Restoration Algorithms on...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Dharmesh Dhabliya Rajat Saini Dhyan Yadav Geetha G Baldev Singh T. Sripriya Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India School of Computer Science and Engineering Jain (Deemed to be University) Bangalore Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

This study examines the effect of various image recovery algorithms on photo great in digital photo processing. Especially, the consequences on the visual quality of the photographs are studied through diverse metrics along with contrast, brightness, sharpness, and color saturation. Additionally, the algorithms are compared to every other as a way to decide which algorithm produces the quality effects. The studies will use images from public picture databases and effects can be gathered the use of photo first-rate evaluation software. Moreover, diverse noise and distortion distortions are applied to the photos to be able to investigate the impact of the distinctive algorithms on them. By means of determining variations in photograph first-rate, beneficial insights at the performance of numerous image recuperation algorithms can be obtained. In conclusion, this studies will offer a complete evaluation of the performance of diverse picture recovery algorithms utilized in digital photograph processing. losing light on which algorithms satisfactory enhance the visual nice of snap shots.

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Quantum Edge Detection and Convolution Using Paired Transform-Based image Representation

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INFORMATION 2025年第4期16卷 255-255页

作者： Grigoryan, Artyom Gomez, Alexis Agaian, Sos Panetta, Karen Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA CUNY Sch Engn Dept Comp Sci New York NY 10031 USA Tufts Univ Sch Engn Dept Elect & Comp Engn Medford MA 02155 USA

Classical edge detection algorithms often struggle to process large, high-resolution image datasets efficiently. Quantum image processing.offers a promising alternative, but current implementations face significant challenges, such as time-consuming data acquisition, complex device requirements, and limited real-time processing.capabilities. This work presents a novel paired transform-based quantum representation for efficient image processing. This representation enables the parallelization of convolution operations, simplifies gradient calculations, and facilitates the processing.of one-dimensional and two-dimensional signals. We demonstrate that our approach achieves improved processing.speed compared to classical methods while maintaining comparable accuracy. The successful implementation of real-world images highlights the potential of this research for large-scale quantum image processing. architecture-specific optimizations, and applications beyond edge detection.

关键词： quantum convolution quantum Fourier transform quantum paired transform quantum gradient

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digital image processing.methods for the evaluation of optical anisotropy effects in tempered architectural glass using photoelastic measurements

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GLASS STRUCTURES & ENGINEERING 2021年第1期6卷 3-19页

作者： Dix, S. Mueller, P. Schuler, C. Kolling, S. Schneider, J. Univ Appl Sci Inst Mat & Bldg Res Munich Germany THM Univ Appl Sci Inst Mech & Mat Giessen Germany Tech Univ Darmstadt Inst Struct Mech & Design Darmstadt Germany

In the present paper, optical anisotropy effects in architectural glass are evaluated using digital image processing. Hereby, thermally toughened glass panes were analyzed quantitatively using a circular polariscope. Glass subjected to externally applied stresses or residual stresses becomes birefringent. Polarized light on birefringent materials causes interference colors (iridescence), referred to as anisotropies, which affect the optical appearance of glass panes in building envelopes. Thermally toughened glass, such as toughened safety glass or heat strengthened glass, show these iridescences due to thermally induced residual stress differences. RGB-photoelastic full-field methods allow the quantitative measurement of anisotropies, since the occurring interference colors are related to the measured retardation values. By calibrating the circular polariscope, retardation images of thermally toughened glass panes are generated from non-directional isochromatic images using computer algorithms. The analysis of the retardation images and the evaluation of the anisotropy quality of the glass is of great interest in order to detect and sort out very low quality glass panes directly in the production process. Therefore, in this paper retardation images are acquired from different thermally toughened glass panes then different image processing.methods are presented and applied. It is shown that a general definition of exclusion zones, e.g. near edges is required prior to the evaluation. In parallel, the limitations in the application of first-order statistical and threshold methods are presented. The intend of the investigation is the extension of the texture analysis based on the generation of Grey Level Co-occurrence Matrices, where the spatial arrangement of the retardation values is considered in the evaluation. For the first time, the results of textural features of different glass pane formats could be compared using reference areas and geometry factors. By reduct

关键词： Glass stress Thermal tempering Anisotropy digital image processing Quality control

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