Improving Digital Satellite Image for security purposes

Huda Hamdan Ali
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Abstract

Satellite imagery is employed in many different fields of study. These pictures have serious quality problems. Image enhancement algorithms, however, can improve it in terms of contrast, brightness, feature elimination from noise contents, etc. These algorithms present and analyse the picture's properties by sharpening, focusing, or smoothing the image. Therefore, the specific application determines the goal of picture enhancement. This paper briefly overviews picture enhancement methods that produce optimal and progressive outcomes for satellite images used for secured remote sensing. To do this, various image enhancement techniques are used, which are widely used today to improve image quality across various image processing applications. Some commonly used image enhancement techniques include spatial filtering, contrast stretching, and histogram equalisation. These techniques aim to enhance the visual quality of satellite images by adjusting brightness and contrast and reducing noise. These methods can also improve the interpretability of the images for remote sensing purposes. The enhancement of satellite images finds use in several fields, particularly security. It is essential for security applications, including threat detection, border control, and surveillance. Security professionals may more effectively analyse and understand data to spot any dangers or questionable activity by boosting the visual details and general quality.   Keywords: Satellite image analysis; mean filter; secured application; SVM; wavelet transformation
为安全目的改进数字卫星图像
卫星图像被用于许多不同的研究领域。这些图像存在严重的质量问题。然而,图像增强算法可以在对比度、亮度、消除噪点特征等方面对其进行改进。这些算法通过锐化、聚焦或平滑图像来呈现和分析图像的特性。因此,具体应用决定了图像增强的目标。本文简要概述了可为用于安全遥感的卫星图像产生最佳和渐进结果的图像增强方法。为此,本文采用了各种图像增强技术,这些技术在当今各种图像处理应用中被广泛用于提高图像质量。一些常用的图像增强技术包括空间滤波、对比度拉伸和直方图均衡化。这些技术旨在通过调整亮度和对比度以及减少噪音来提高卫星图像的视觉质量。这些方法还能提高图像在遥感方面的可解释性。卫星图像增强可用于多个领域,尤其是安全领域。它对安全应用至关重要,包括威胁检测、边境控制和监视。通过增强视觉细节和总体质量,安全专业人员可以更有效地分析和理解数据,发现任何危险或可疑活动。关键词卫星图像分析;均值滤波;安全应用;SVM;小波变换
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