一种新的退化图像恢复方法

Tripty Singh
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引用次数: 13

摘要

尽管近年来提出了一些复杂的方法,但退化图像的恢复技术仍然是一项具有挑战性的任务。当图像模型符合算法假设,但不能保留图像的边缘和精细结构时,均表现出优异的性能。本文提出了一种新的图像恢复方法。为了对这种新型恢复程序进行性能分析,开发了图形用户界面。展示了不同滤波器对不同噪声下退化图像的恢复效果。在该方法的实现中,首先通过在样本图像中添加不同类型的噪声,然后使用不同类型的滤波器(均值滤波器,最小滤波器和最大滤波器)对图像进行卷积来降低图像的质量。提出了图像复原方法,对图像去噪技术的性能进行了分析,并在图形用户界面上进行了研究。本文用不同的噪声对真彩色样本图像进行退化,然后对其进行复原。利用目前最先进的技术,从均方误差、峰值信噪比和归一化绝对误差等方面对该方法进行了性能分析。与现有方法相比,该方法具有更好的优化效果,适用于更大范围的噪声。
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Novel Restoration Process for Degraded Image
Restoration techniques of degraded image is still a challenging task, in spite of the sophistication of the recently proposed methods. All show an outstanding performance when the image model corresponds to the algorithm assumptions but fail to retain the edges and fine structure. In this paper, a novel approach for image restoration has been developed. To show the analysis of performance of this noel restoration procedure GUI has been developed. It shows the Restoration of Degraded image on various noises by different Filters. In implementation of the approach first, image is degraded by adding different types of noises in sample images and then convolving images with different kinds of filters (Mean Filters, Min and Max Filters). Proposed image restoration method's analysis on performances of denoising techniques Graphical User Interface has been developed as a part of this research. In this paper true colour sample images are degraded with different noise and then is restored back. The performance analyis of the present approach with state of art techniques are in terms of mean square error, peak signal-to-noise ratio, and normalized absolute error is also provided. In comparisons with other state of art methods, present approach yields better to optimization, and shows to be applicable to a much wider range of noises.
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