A Very High Throughput Deblocking Filter for H.264/AVC

Kthiri, Moez; Gal, Bertrand Le; Kadionik, Patrice; Atitallah, Ahmed Ben

doi:10.1007/s11265-013-0744-4

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…Using a Low-Level Synthesis design, the Register Transfer Level (RTL) description may be adjusted to generate an excellent and efficient netlist. Developing an RTL description is arduous and time-consuming, particularly for complicated applications [52][53][54]. In fact, each low-level circuit's operations must be specified.…”

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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“…The density of Field Programmable Gate Arrays (FPGAs) has increased over time, enabling hardware implementation of complex applications across various fields, such as IoT systems [20], video processing [21,22], and neural networks [23]. To reduce the design complexity of FPGAs, High-Level Synthesis (HLS) flow can be employed instead of Low-Level Synthesis (LLS) flow, allowing for efficient exploration of an algorithm's design space and increased designer productivity [24,25].…”

Section: Introductionmentioning

confidence: 99%

Accelerated FPGA-Based Vector Directional Filter for Real-Time Color Image Denoising with Enhanced Performance

Alanazi¹

2023

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This paper presents an accelerated implementation of the Vector Directional Filter (VDF) on a Field Programmable Gate Array (FPGA) for real-time denoising of color images. The VDF effectively suppresses noise while preserving edges and fine details, making it ideal for a range of applications such as satellite and multispectral biomedical imaging. However, the filter's high computational complexity poses challenges for real-time processing. Existing solutions either fail to meet real-time execution requirements or compromise image quality through hardware implementation approximations. To overcome these challenges, we first model the VDF using C/C++ programming, and subsequently design an efficient floating-point hardware architecture employing the High-Level Synthesis (HLS) flow. Optimal directives are selected using the Xilinx Vivado HLS tool. The VDF architecture is then integrated as a coprocessor with the Cortex-A53 hardcore processor in the XCZU9EG FPGA. To enhance data bandwidth between software and hardware components, three Direct Memory Access (DMAs) units are utilized to transfer three image lines in parallel. Furthermore, internal memory is implemented on the XCZU9EG FPGA, providing increased flexibility for managing the restored image. The VDF Software/Hardware (SW/HW) design's robustness and accuracy are validated through experimental studies on the ZCU102 board. Our design accelerates the filtering process by 21 times, maintaining visual quality and effectively removing noise from color images compared to the VDF SW design. Additionally, our solution outperforms existing approaches in terms of filtered image quality and processing time, showing a 24% improvement in the worst-case scenario.

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“…With LLS design, the Register Transfer Level (RTL) description can be modified to produce an excellent, efficient netlist. However, creating such an RTL description takes a lot of work and time, especially for complicated applications [ 50 , 51 , 52 ]. This is because each low-level circuit’s activities must be described.…”

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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A Very High Throughput Deblocking Filter for H.264/AVC

Cited by 10 publications

References 11 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

Accelerated FPGA-Based Vector Directional Filter for Real-Time Color Image Denoising with Enhanced Performance

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

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