An Optimized SW/HW AVMF Design Based on High-Level Synthesis Flow for Color Images

Alanazi, Turki M.; Atitallah, Ahmed Ben; Abid, Imen

doi:10.32604/cmc.2021.017575

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…Complex systems can only be developed by hardware designers with specific knowledge and abilities. In order to simplify the complexity of the FPGA design, Low-Level Synthesis must be replaced by High-Level Synthesis (HLS) [55][56][57]. Using software high-level languages (systemC, C/C + +, etc.…”

Section: Introductionmentioning

confidence: 99%

New Real-Time High-Density Impulsive Noise Removal Method Applied to Medical Images

et al. 2023

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This paper introduces a new method for real-time high-density impulsive noise elimination applied to medical images. A double process aimed at the enhancement of local data composed of Nested Filtering followed by a Morphological Operation (NFMO) is proposed. The major problem with heavily noisy images is the lack of color information around corrupted pixels. We show that the classic replacement techniques all come up against this problem, resulting in average restoration quality. We only focus on the corrupt pixel replacement phase. For the detection itself, we use the Modified Laplacian Vector Median Filter (MLVMF). To perform pixel replacement, two-window nested filtering is suggested. All noise pixels in the neighborhood scanned by the first window are investigated using the second window. This investigation phase increases the amount of useful information within the first window. The remaining useful information that the second window failed to produce in the case of a very strong connex noise concentration is then estimated using a morphological operation of dilatation. To validate the proposed method, NFMO is first evaluated on the standard image Lena with a range of 10% to 90% impulsive noise. Using the Peak Signal-to-Noise Ratio metric (PSNR), the image denoising quality obtained is compared to the performance of a wide variety of existing approaches. Several noisy medical images are subjected to a second test. In this test, the computation time and image-restoring quality of NFMO are assessed using the PSNR and the Normalized Color Difference (NCD) criteria. Finally, an optimized design for a field-programmable gate array (FPGA) is suggested to implement the proposed method for real-time processing. The proposed solution performs excellent quality restoration for images with high-density impulsive noise. When the proposed NFMO is used on the standard Lena image with 90% impulsive noise, the PSNR reaches 29.99 dB. Under the same noise conditions, NFMO completely restores medical images in an average time of 23 milliseconds with an average PSNR of 31.62 dB and an average NCD of 0.10.

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Section: Introductionmentioning

confidence: 99%

New Real-Time High-Density Impulsive Noise Removal Method Applied to Medical Images

et al. 2023

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“…Nevertheless, only hardware designers with specialized knowledge and abilities are capable of creating a sophisticated system. Therefore, in order to decrease the complexity of the FPGA design, it is imperative to go from Low-Level Synthesis (LLS) to High-Level Synthesis (HLS) [ 53 , 54 , 55 ]. The HLS tool synthesizes the formalized algorithms into a behavioral and structural RTL hardware description utilizing software high-level languages (systemC, C/C++, etc.).…”

Section: Introductionmentioning

confidence: 99%

New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images

et al. 2022

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In this paper, we propose a new Modified Laplacian Vector Median Filter (MLVMF) for real-time denoising complex images corrupted by “salt and pepper” impulsive noise. The method consists of two rounds with three steps each: the first round starts with the identification of pixels that may be contaminated by noise using a Modified Laplacian Filter. Then, corrupted pixels pass a neighborhood-based validation test. Finally, the Vector Median Filter is used to replace noisy pixels. The MLVMF uses a 5 × 5 window to observe the intensity variations around each pixel of the image with a rotation step of π/8 while the classic Laplacian filters often use rotation steps of π/2 or π/4. We see better identification of noise-corrupted pixels thanks to this rotation step refinement. Despite this advantage, a high percentage of the impulsive noise may cause two or more corrupted pixels (with the same intensity) to collide, preventing the identification of noise-corrupted pixels. A second round is then necessary using a second set of filters, still based on the Laplacian operator, but allowing focusing only on the collision phenomenon. To validate our method, MLVMF is firstly tested on standard images, with a noise percentage varying from 3% to 30%. Obtained performances in terms of processing time, as well as image restoration quality through the PSNR (Peak Signal to Noise Ratio) and the NCD (Normalized Color Difference) metrics, are compared to the performances of VMF (Vector Median Filter), VMRHF (Vector Median-Rational Hybrid Filter), and MSMF (Modified Switching Median Filter). A second test is performed on several noisy chest x-ray images used in cardiovascular disease diagnosis as well as COVID-19 diagnosis. The proposed method shows a very good quality of restoration on this type of image, particularly when the percentage of noise is high. The MLVMF provides a high PSNR value of 5.5% and a low NCD value of 18.2%. Finally, an optimized Field-Programmable Gate Array (FPGA) design is proposed to implement the proposed method for real-time processing. The proposed hardware implementation allows an execution time equal to 9 ms per 256 × 256 color image.

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Unified FPGA Design for the HEVC Dequantization and Inverse Transform Modules

Alanazi¹,

Atitallah²

2022

Computers, Materials &Amp; Continua

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As the newest standard, the High Efficiency Video Coding (HEVC) is specially designed to minimize the bitrate for video data transfer and to support High Definition (HD) and ULTRA HD video resolutions at the cost of increasing computational complexity relative to earlier standards like the H.264. Therefore, real-time video decoding with HEVC decoder becomes a challenging task. However, the Dequantization and Inverse Transform (DE/IT) are one of the computationally intensive modules in the HEVC decoder which are used to reconstruct the residual block. Thus, in this paper, a unified hardware architecture is proposed to implement the HEVC DE/IT module for all Transform Unit (TU) block size, including 4 × 4, 8 × 8, 16 × 16 and 32 × 32. This architecture is designed using the High-Level Synthesis (HLS) and the Low-Level Synthesis (LLS) methods in order to compare and determine the best method to implement in real-time the DE/IT module. In fact, the C/C++ programming language is used to generate an optimized hardware design for DE/IT module through the Xilinx Vivado HLS tool. On the other hand, the LLS hardware architecture is designed by the VHSIC Hardware Description language (VHDL) and using the pipeline technique to decrease the processing time. The experimental results on the Xilinx XC7Z020 FPGA show that the LLS design increases the throughput in term of frame rate by 80% relative to HLS design with a 4.4% increase in the number of Look-Up Tables (LUTs). Compared with existing related works in literature, the proposed architectures demonstrate significant advantages in hardware cost and performance improvement.

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An Optimized SW/HW AVMF Design Based on High-Level Synthesis Flow for Color Images

Cited by 4 publications

References 20 publications

New Real-Time High-Density Impulsive Noise Removal Method Applied to Medical Images

New Real-Time High-Density Impulsive Noise Removal Method Applied to Medical Images

New Real-Time Impulse Noise Removal Method Applied to Chest X-ray Images

Unified FPGA Design for the HEVC Dequantization and Inverse Transform Modules

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