{"title":"Recent trends in pixel-based image enhancement techniques using VLSI cores – a review","authors":"Chrishia Christudhas, Annis Fathima A","doi":"10.1016/j.rineng.2025.104481","DOIUrl":null,"url":null,"abstract":"<div><div>Image processing is widely used in biometrics, medicine, agriculture, robotics, computer vision and other domain applications. Based on recent trends, the need for obtaining good-quality images with standalone architecture is in demand. Image enhancement techniques are applied to low-contrast or degraded images to improve their quality, while VLSI serves as a processing platform for real-time images as they are more speed-efficient. This paper meticulously studies various state-of-the-art pixel-based image enhancement techniques, including studies incorporating VLSI cores. Experimental research and implementation of pixel-based enhancement techniques are carried out in Xilinx ISE, along with their power, area and delay analysis. The techniques were implemented using the Spartan6 FPGA device in Xilinx ISE 14.7 design tool. The enhancement techniques were tested, and the results from MATLAB are included to provide a better understanding of these techniques. It is observed that Histogram Sliding achieves better area utilization. In terms of delay, Histogram Stretching proves more efficient. Histogram Equalization and its variants prove more power efficient than other state-of-the-art methods. This paper highlights the importance of VLSI in image processing.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"25 ","pages":"Article 104481"},"PeriodicalIF":7.9000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590123025005596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Image processing is widely used in biometrics, medicine, agriculture, robotics, computer vision and other domain applications. Based on recent trends, the need for obtaining good-quality images with standalone architecture is in demand. Image enhancement techniques are applied to low-contrast or degraded images to improve their quality, while VLSI serves as a processing platform for real-time images as they are more speed-efficient. This paper meticulously studies various state-of-the-art pixel-based image enhancement techniques, including studies incorporating VLSI cores. Experimental research and implementation of pixel-based enhancement techniques are carried out in Xilinx ISE, along with their power, area and delay analysis. The techniques were implemented using the Spartan6 FPGA device in Xilinx ISE 14.7 design tool. The enhancement techniques were tested, and the results from MATLAB are included to provide a better understanding of these techniques. It is observed that Histogram Sliding achieves better area utilization. In terms of delay, Histogram Stretching proves more efficient. Histogram Equalization and its variants prove more power efficient than other state-of-the-art methods. This paper highlights the importance of VLSI in image processing.
图像处理广泛应用于生物识别、医学、农业、机器人、计算机视觉等领域。根据最近的趋势,人们需要通过独立架构获得高质量的图像。图像增强技术应用于低对比度或退化的图像,以提高其质量,而超大规模集成电路作为实时图像的处理平台,因为它们具有更高的速度效率。本文细致地研究了各种最先进的基于像素的图像增强技术,包括集成VLSI内核的研究。在Xilinx ISE中进行了基于像素的增强技术的实验研究和实现,以及它们的功率,面积和延迟分析。这些技术在Xilinx ISE 14.7设计工具中使用Spartan6 FPGA器件实现。对增强技术进行了测试,并包括MATLAB的结果,以便更好地理解这些技术。观察到直方图滑动可以获得更好的面积利用率。在延迟方面,直方图拉伸被证明更有效。直方图均衡化及其变体证明比其他最先进的方法更节能。本文强调了超大规模集成电路在图像处理中的重要性。