Christudhas Chrishia, Fathima Annis
School of Electronics Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.
Sci Rep. 2024 Nov 19;14(1):28628. doi: 10.1038/s41598-024-80053-6.
The prominence of image processing in today's cutting-edge technology is undeniable. Integrating software with hardware leverages both strengths, resulting in a real-time processing system that is efficient and streamlined. Raw images are usually affected by noise, which hinders the acquisition of good-quality and detailed images; hence, denoising becomes necessary. This paper proposes a modified min-max median (MMM) filter to remove impulse noise and a Tritonic sorter to localize corrupted pixels. The proposed denoising method focuses on localizing noisy pixels, unlike traditional denoising approaches, which focus only on noise detection and filtering. A min-max sheet provides the location of the corrupted pixels, and filtering is performed on them. The Tritonic Sorter, consisting of a max locator and a min locator, compares three input values and finds the minimum, maximum and median values among them. Compared to other state-of-the-art methods, the proposed method minimizes the number of comparators needed to carry out the sorting process. The proposed method was synthesized in the ZedBoard Zynq kit using the Vivado tool. The results show that the area improved by 27%, and the power improved by 16.23% compared with those of the existing method.
图像处理在当今前沿技术中的突出地位是不可否认的。将软件与硬件集成利用了两者的优势，从而产生了一个高效且精简的实时处理系统。原始图像通常会受到噪声的影响，这会阻碍高质量和详细图像的获取；因此，去噪变得必要。本文提出了一种改进的最小 - 最大中值（MMM）滤波器来去除脉冲噪声，并提出了一种Tritonic排序器来定位损坏的像素。与传统的仅专注于噪声检测和滤波的去噪方法不同，所提出的去噪方法专注于定位噪声像素。一个最小 - 最大表提供了损坏像素的位置，并对它们进行滤波。由一个最大定位器和一个最小定位器组成的Tritonic排序器比较三个输入值，并找出其中的最小值、最大值和中值。与其他现有技术方法相比，所提出的方法将执行排序过程所需的比较器数量减到最少。所提出的方法使用Vivado工具在ZedBoard Zynq套件中进行了综合。结果表明，与现有方法相比，面积提高了27%，功耗提高了16.23%。
