利用各种滤波器对IRS-P6卫星Liss IV遥感数据进行图像增强和性能评估

IF 0.9 4区 地球科学 Q4 GEOCHEMISTRY & GEOPHYSICS
Geofizika Pub Date : 2015-12-31 DOI:10.15233/GFZ.2015.32.11
T. Kumar, D. Murugan, K. Rajalakshmi, T. I. Manish
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引用次数: 7

摘要

针对印度P6 Liss 4遥感卫星近红外波段遥感数据,提出了快速有效的图像增强滤波技术。基于空域滤波器和频域滤波器的图像增强滤波技术主要有中值滤波器、维纳滤波器、双边滤波器和高斯同态滤波器,以及与滤波器配合使用的椒盐噪声和高斯噪声。选取图像进行测试,并基于PSNR性能度量值和从这些滤波器中确定的最佳滤波技术。最后,高斯同态滤波技术适用于Liss IV遥感近红外波段的图像增强。图像增强技术是对边缘检测和图像分割等后续工作的预处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image enhancement and performance evaluation using various filters for IRS-P6 Satellite Liss IV remotely sensed data
This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic filter and selected noises salt and pepper and Gaussian noise used with filter. Selected images tested with each filter and based on PSNR performance metric value and best filtering technique identified from these filters. Finally, Gaussian homomorphic filtering technique is suitable for image enhancement of the Liss IV remotely sensed Near-Infrared band. Image enhancement technique is preprocessing for future work such as edge detection and image segmentation.
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来源期刊
Geofizika
Geofizika 地学-地球化学与地球物理
CiteScore
1.60
自引率
0.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: The Geofizika journal succeeds the Papers series (Radovi), which has been published since 1923 at the Geophysical Institute in Zagreb (current the Department of Geophysics, Faculty of Science, University of Zagreb). Geofizika publishes contributions dealing with physics of the atmosphere, the sea and the Earth''s interior.
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