Contrast enhancement of dark images using stochastic resonance

Jha R.K.

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Contrast enhancement of dark images using stochastic resonance

机译：使用随机共振增强暗图像的对比度

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Two stochastic resonance (SR)-based techniques are introduced for enhancement of very low-contrast images. In the proposed SR-based image enhancement technique-1, an expression for optimum threshold has been derived. Gaussian noise of increasing standard deviation has been added iteratively to the low-contrast image until the quality of enhanced image reaches maximum. A quantitative parameter `distribution separation measure (DSM)` is used to measure the enhancement quality. In order to reduce the required number of iterations in the second enhancement technique the author`s have derived an expression for optimum noise standard deviation `_optimum that maximises signal-to-noise ratio (SNR). Image enhancement is obtained by iterating only with few noise standard deviations around σ_optimum. This reduces number of iterations drastically. Comparison with the existing methods shows the superiority of the proposed method.

机译：引入了两种基于随机共振（SR）的技术来增强非常低对比度的图像。在提出的基于SR的图像增强技术-1中，已经导出了最佳阈值的表达式。反复将标准偏差增加的高斯噪声添加到低对比度图像中，直到增强图像的质量达到最大为止。定量参数“分布分离度量（DSM）”用于度量增强质量。为了减少第二种增强技术中所需的迭代次数，作者已经导出了最佳信噪比（_{optimum ）的表达式，该表达式最大化了信噪比（SNR）。通过仅在σ_{optimum 周围只有很少的噪声标准偏差进行迭代，即可获得图像增强效果。这样可以大大减少迭代次数。与现有方法的比较表明了该方法的优越性。}}

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《Image Processing, IET》 |2012年第3期|p.230-237|共8页
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Jha R.K.;
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Contrast enhancement of dark images using stochastic resonance

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