基于中值金字塔变换的图像逆半调

Inverse halftoning based on the median pyramid

针对误差分散半调的系统特征,构建了一种基于非线性中值算子的多分辨金字塔变换.研究了变换后各级近似、细节信号中半调噪声的分布特性和消噪方法,提出了一种用wiener滤波抑制一级细节中半调噪声,并用消噪后的细节与近似信号重构连续色调图像的逆半调算法.实验结果表明,该变换具有较好的信噪分离能力,比线性多尺度变换更适合于逆半调.新逆半调算法的时空间复杂度较低,其结果的峰值信噪比值及去噪保沿效果良好.

Focused on the property of error diffuse halftoning, a multi-scale pyramid transform for two dimensions is constructed by the nonlinear median operator. Using the transform distribution of halftone noise in approximations and details on each-scale and its de-noising method are studied through many experiments, and a novel inverse halftoning algorithm via median pyramid transform is proposed. The method firstly decomposes the halftoning image by the transform in one-scale, and a wiener filter is applied to the detail coefficients. Then an inverse image is reconstructed from the cleaned details and approximations. Experimental results demonstrate that the proposed transform can separate the halftone noise and details better than the linear multi-scale transform. The proposed algorithm has the efficient edge preserving ability while smoothing the halftone patterns, excellent PSNR performance, low time complexity and small memory requirement.