二维最小均方自适应图像恢复方法

P. Manyere, A. L. Nel
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引用次数: 0

摘要

利用图像进行信息采集的成功与否取决于采集设备的消噪能力。由于买不起卫星,大多数第三世界国家依靠悬挂在飞机上的摄像头来收集信息。像Vinten这样的相机,可以从1000米左右的高度拍摄详细的照片。这种机载相机的使用导致处理时间长,在处理过程中丢失重要信息,造成图像质量差。为了解决这些挑战,本文开发了能够恢复损坏或质量差的图像的软件,以便轻松快速地解释。利用MATLAB实现了二维最小均方(LMS)自适应算法对受损图像进行恢复。结果表明,对退化的图像进行直线增强,可以改善图像的性能。二维自适应算法提高了退化图像的质量。对损坏和恢复图像的进一步分析显示频率响应的相关移位和图像强度大小的损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image recovery by 2-D Least Mean Square adaptive method
The success of information gathering using images depends on the ability of the gathering device to eliminate noise. The majority of third world countries rely on under slung aircraft cameras to gather information, because of their inability to afford satellites. The camera such as Vinten, can take detailed pictures from an altitude of about 1000 m. Use of such airborne cameras result in long processing time, loss of important information during processing, causing poor quality images. To address these challenges, this paper developed software that is capable of restoring damaged or poor quality images for ease and quick interpretation. The 2-D Least Mean Square (LMS) adaptive algorithm was implemented using MATLAB to restore damaged images. The results showed an improvement by line enhancement on the degraded images. The 2-D adaptive algorithm improved quality of degraded images. A further analysis of the damaged and restored images showed an associated shift in frequency response and the loss in the intensity magnitude of the image.
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