CORRECTION OF A NOISY IMAGE BY A POLYNOMIAL APPROACH AND CHOICE OF THE BEST IMAGE BY ONE OF THE POLYNOMIAL’S ROOTS.

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Abstract

In this paper a polynomial method of selecting an image disturbed and corrected by the modified power law by one of its roots, is proposed. This power law uses here is a real power variable belonging to the interval [1.00,..1.12]. It provides a dozen corrected images. But it is difficult to get the best image between them, or the image which has the best signal to noise ratio. One of the roots provides this value. Comparison of reconstructed image with the original is proved by structural similarity index (SSIM), entropy and peak signal-to-noise ratio (PSNR) which are objective quality measures and the averages of gray levels of pixels which are very similar. The polynomial selection method has the advantage of providing only a single corrected image without RGB YCbCr transformation noise and close to original among many others. Where somebody needs to choose one image among several, this method can provide solution.
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用多项式方法校正噪声图像,并根据多项式的一个根选择最佳图像。
本文提出了一种多项式方法来选择被修正幂律扰动并通过幂律的一个根进行校正的图像。这个幂律在这里使用的是一个属于区间[1.00,..1.12]的实数幂变量。它提供了一打校正图像。但是很难在两者之间获得最佳图像,或者具有最佳信噪比的图像。其中一个根提供这个值。利用结构相似指数(SSIM)、熵和峰值信噪比(PSNR)作为客观质量指标,以及非常相似像素的灰度均值,证明了重建图像与原始图像的比较。多项式选择方法的优点是只提供一幅校正后的图像,没有RGB / YCbCr变换噪声,并且与原始图像接近。当需要从多个图像中选择一个图像时,该方法可以提供解决方案。
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