HSMF:用于去除高密度椒盐噪声的硬件高效单级反馈均值滤波器

IF 2.9 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Midde Venkata Siva, E. P. Jayakumar
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引用次数: 0

摘要

噪点是一种对数字图像质量有负面影响的干扰因素。椒盐噪点是噪点的一种,可能出现在图像采集或传输的任何时候。利用适当的修复程序来减少噪声至关重要。本文为基于反馈决策的修剪均值滤波器提出了一种硬件高效 VLSI 架构,可消除图像中的高密度椒盐噪声。通过考虑与噪声中心像素相对应的 3 \(\times\) 3 窗口中的邻近像素来识别和修正噪声像素。计算窗口中水平和垂直噪声像素的平均值或无噪声像素的平均值。这个平均值会被反馈回来,噪声中心像素也会立即更新,更新后的像素值将被用于修正其余的损坏像素。据观察,即使噪声密度很高,这一程序也能有效去除噪声像素。此外,所设计的 VLSI 架构非常高效,因为该算法不需要排序过程,与其他最先进的算法相比,所需的计算资源更少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

HSMF: hardware-efficient single-stage feedback mean filter for high-density salt-and-pepper noise removal

HSMF: hardware-efficient single-stage feedback mean filter for high-density salt-and-pepper noise removal

Noise is an unwanted element that has a negative impact on digital image quality. Salt-and-pepper noise is a type of noise that can appear at any point during the acquisition or transmission of images. It is essential to utilize proper restoration procedures to lessen the noise. This paper proposes a hardware-efficient VLSI architecture for the feedback decision-based trimmed mean filter that eliminates high-density salt-and-pepper noise in the images. The noisy pixels are identified and corrected by considering the neighbouring pixels in a 3 \(\times\) 3 window corresponding to this noisy centre pixel. Either the mean of the horizontal and vertical noisy pixels or the mean of noise-free pixels in the window is computed. This mean value is fed back and the noisy centre pixel is updated immediately, such that this updated pixel value is used henceforth for correcting the remaining corrupted pixels. It is observed that this procedure helps in removing the noisy pixels effectively even if the noise density is high. Additionally, the designed VLSI architecture is efficient, since the algorithm does not require a sorting process and the computing resources required are less when compared to other state-of-the-art algorithms.

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来源期刊
Journal of Real-Time Image Processing
Journal of Real-Time Image Processing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
6.80
自引率
6.70%
发文量
68
审稿时长
6 months
期刊介绍: Due to rapid advancements in integrated circuit technology, the rich theoretical results that have been developed by the image and video processing research community are now being increasingly applied in practical systems to solve real-world image and video processing problems. Such systems involve constraints placed not only on their size, cost, and power consumption, but also on the timeliness of the image data processed. Examples of such systems are mobile phones, digital still/video/cell-phone cameras, portable media players, personal digital assistants, high-definition television, video surveillance systems, industrial visual inspection systems, medical imaging devices, vision-guided autonomous robots, spectral imaging systems, and many other real-time embedded systems. In these real-time systems, strict timing requirements demand that results are available within a certain interval of time as imposed by the application. It is often the case that an image processing algorithm is developed and proven theoretically sound, presumably with a specific application in mind, but its practical applications and the detailed steps, methodology, and trade-off analysis required to achieve its real-time performance are not fully explored, leaving these critical and usually non-trivial issues for those wishing to employ the algorithm in a real-time system. The Journal of Real-Time Image Processing is intended to bridge the gap between the theory and practice of image processing, serving the greater community of researchers, practicing engineers, and industrial professionals who deal with designing, implementing or utilizing image processing systems which must satisfy real-time design constraints.
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