图像增强器

Atul, Pardeep, Manjit Kaur
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引用次数: 1

摘要

图像处理使用机器学习算法和OpenCV(开放计算机视觉的缩写)等工具完成。本文提出了一种改进的、方便的图像处理方法。在当今时代,任何方式或噪音都高度扭曲的图像太常见了。这个问题可以由太多的原因引起,无论是从一个源到另一个源的传输,物理设备损坏,信号从源解码不良,甚至是设备传感器的噪声。在计算机和Photoshop等应用程序发明之前,这些工作显然只能由在这些领域具有丰富知识的专家来完成。它们主要用于处理图像的物理副本,如通过刷刷技术增强图像。为了消除不需要的噪声,提高图像质量,提出了一种结合k均值和PCA的基于决策的滤波策略。现在,在许多免费的编辑工具中有各种各样的过滤器,它们确实可以按照你想要的方式提高图像的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Enhancer
Image processing is done using machine learning algorithms and tools like OpenCV (short for Open Computer Vision). This research paper shows an improved and convenient approach towards processing of images. Images that are highly distorted by any means or noise are too common in todays' era. This problem can rise by too many reasons be it transmitting from one source to another, by physical device damages, signals poor decoding from the source and even the noise from the sensor of the device they are taken. Prior to the invention of computers and applications such as Photoshop, these jobs were clearly performed only by experts with extensive knowledge in these areas. They mainly used to process physical copies of the images like enhancing the images by brushing techniques. For eliminating undesired noises and thus providing higher image quality, a new decision-based filtering strategy combining K-means and PCA is proposed. Now a days, there are various filters available in many free editing tools that surely do enhance the quality of the image the way you want them to be.
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