An FPGA-based design for a real-time image denoising using approximated fractional integrator

Kumar, Sumit; Jha, Rajib Kumar

doi:10.1007/s11045-020-00709-0

Cited by 12 publications

(3 citation statements)

References 47 publications

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“…An approximated fractional integrator-based denoising algorithm (AFI) was developed by Kumar and Jha [8]. Two types of images (grayscale and binary images) were considered for their experiment.…”

Section: Literature Reviewmentioning

confidence: 99%

FPGA based secure and noiseless image transmission using LEA and optimized bilateral filter

Hebbale

Akula²,

Baraki³

2022

csci

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In today’s world, the transmission of secured and noiseless image is a difficult task. Therefore, effective strategies are important to secure the data or secret image from the attackers. Besides, denoising approaches are important to obtain noise-free images. For this, an effective crypto-steganography method based on Lightweight Encryption Algorithm (LEA) and Modified Least Significant Bit (MLSB) method for secured transmission is proposed. Moreover, a bilateral filter-based Whale Optimization Algorithm (WOA) is used for image denoising. Before image transmission, the secret image is encrypted by the LEA algorithm and embedded into the cover image using Discrete Wavelet Transform (DWT) and MLSB technique. After the image transmission, the extraction process is performed to recover the secret image. Finally, a bilateral filter-WOA is used to remove the noise from the secret image. The Verilog code for the proposed model is designed and simulated in Xilinx software. Finally, the simulation results show that the proposed filtering technique has superior performance than conventional bilateral filter and Gaussian filter in terms of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM).

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Section: Literature Reviewmentioning

confidence: 99%

FPGA based secure and noiseless image transmission using LEA and optimized bilateral filter

Hebbale

Akula²,

Baraki³

2022

csci

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“…The disadvantage of the adaptive median filter cannot distinguish the fine details from the noise. Kumar and Jha (2020) have suggested the image denoising algorithm depends on approximated fractional integrator. In this enactment of texture and edge detection, enoising image was closer to the original image.…”

Section: Literature Surveymentioning

confidence: 99%

A field programmable gate array-based biomedical noise reduction framework using advanced trilateral filter

Raja

Naveen

Palaniswamy

et al. 2021

Transactions of the Institute of Measurement and Control

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Filtering is one of the essential tools utilized to remove undesirable features in biomedical images. Most biomedical image denoising systems are used for clinical diagnosis. So, in this paper, we use the advanced trilateral filter in the field programmable gate array (FPGA) for removing noise in the biomedical image. Generally, the trilateral filter is used as an edge preserving smoothing filter. This advanced approach of trilateral filter gives the best noise diminution and enhances the image quality. This paper also proposes the hardware implementation of an efficient FPGA-based advanced trilateral filter on real time execution. In this manuscript, we intend to design and implement the FPGA architecture using an advanced trilateral filter. Biomedical images with different noises are used during implementation and compared with the existing bilateral and trilateral architecture to assess the proposed architecture performance. For evaluating the performance metrics of the proposed advanced trilateral filter on MATLAB platform, peak signal-to-noise ratio (PSNR), mean squared error (MSE) and structured similarity index (SSIM) are calculated for different biomedical images – such as brain (MRI), chest (x-ray) and lungs (CT) – with different noises – such as salt and pepper, Gaussian, Poisson and Speckle noises – compared with existing bilateral filter and trilateral filter, respectively. The proposed advanced trilateral filter implementations are checked on Virtex-6, Virtex-7 and Zynq FPGA development board using Verilog programming language in Xilinx ISE 14.5 design tools. The simulation outcomes display that the FPGA execution of the advanced trilateral filter contains better noise removal efficiency in biomedical images compared with the existing bilateral and trilateral filter.

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“…e main research content of this article is roughly divided into five parts. e first part is the introduction, aiming to systematically review the main research topics of this article from the research background, research purpose, research ideas, and methods [13,14]. e second presents Kinect depth image real-time acquisition technology current research principles, details, and system summary.…”

Section: Introductionmentioning

confidence: 99%

Kinect-Based Real-Time Acquisition Algorithm of Crop Growth Depth Images

Shan

Mei

et al. 2021

Mathematical Problems in Engineering

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Kinect 3D sensing real-time acquisition algorithm that can meet the requirements of fast, accurate, and real-time acquisition of image information of crop growth laws has become the trend and necessary means of digital agricultural production management. Based on this, this paper uses Kinect real-time image generation technology to try to monitor and study the depth map of crop growth law in real time, use Kinect to obtain the algorithm of crop growth depth map, and conduct investigation and research. Real-time image acquisition research on crop growth trends provides a basis for in-depth understanding of the application of Kinect real-time image generation technology in research. Kinect image real-time acquisition algorithm is a very important information carrier in agricultural information engineering. The research results show that the real-time Kinect depth image acquisition algorithm can obtain good 3D image data information and can provide valuable data basis for the 3D reconstruction of the later crop growth model, growth status analysis, and real-time monitoring of crop diseases. The data shows that, using Kinect, the real-time feedback speed of crop growth observation can be increased by 45%, the imaging accuracy is improved by 37%, and the related operation steps are simplified by 30%. The survey results show that the crop yield can be increased by about 12%.

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An FPGA-based design for a real-time image denoising using approximated fractional integrator

Cited by 12 publications

References 47 publications

FPGA based secure and noiseless image transmission using LEA and optimized bilateral filter

FPGA based secure and noiseless image transmission using LEA and optimized bilateral filter

A field programmable gate array-based biomedical noise reduction framework using advanced trilateral filter

Kinect-Based Real-Time Acquisition Algorithm of Crop Growth Depth Images

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