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首页> 外文期刊>Journal of visual communication & image representation >Synthesising and reducing film grain
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Synthesising and reducing film grain

机译：合成和还原膜颗粒

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This paper describes some tools for adding and removing film grain. The film grain is represented using an additive signal-dependent model. The approach adopted for artificial grain synthesis avoids subjectivity and an assumption of Gaussianity. The grain within a user-defined plain area is analysed and the synthesis routine generates grain with matching spatial structure having the same probability distribution function as the original. The grain reduction method is based on manipulation of the coefficients achieved using a bi-orthogonal undecimat-ed wavelet decomposition and is extremely advantageous for real-time implementation. The scheme for modifying the coefficient is derived from Bayesian estimation and approximates a range of optimal non-linear functions. Training to deduce parameter values is conducted by contaminating several nominally noise-free images with various realisations of grain noise. Using real and synthetically generated grain noise demonstrated an improvement of objective and visual qualities of the image. The ability of the technique to adapt with respect to image and noise characteristics is also clear.
机译：本文介绍了一些用于添加和删除胶片颗粒的工具。胶片颗粒使用与信号相关的附加模型表示。人工合成谷物所采用的方法避免了主观性和高斯假设。分析用户定义的平原区域内的谷物，合成例程生成具有匹配空间结构的谷物，该空间结构具有与原始对象相同的概率分布函数。晶粒缩减方法基于对使用双正交未抽取小波分解获得的系数的操纵，对于实时实现极为有利。修正系数的方案是从贝叶斯估计中得出的，并且近似了一系列最佳非线性函数。通过用几种不同的谷物噪声实现方式污染几个名义上无噪声的图像来进行演绎以推断参数值。使用真实的和合成产生的颗粒噪声证明了图像的客观和视觉质量的提高。该技术针对图像和噪声特性进行适应的能力也很明显。

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