The University of Texas, Austin, TX 78712-1084, USA.
IEEE Trans Image Process. 2000;9(9):1583-92. doi: 10.1109/83.862639.
Halftones and other binary images are difficult to process with causing several degradation. Degradation is greatly reduced if the halftone is inverse halftoned (converted to grayscale) before scaling, sharpening, rotating, or other processing. For error diffused halftones, we present (1) a fast inverse halftoning algorithm and (2) a new multiscale gradient estimator. The inverse halftoning algorithm is based on anisotropic diffusion. It uses the new multiscale gradient estimator to vary the tradeoff between spatial resolution and grayscale resolution at each pixel to obtain a sharp image with a low perceived noise level. Because the algorithm requires fewer than 300 arithmetic operations per pixel and processes 7x7 neighborhoods of halftone pixels, it is well suited for implementation in VLSI and embedded software. We compare the implementation cost, peak signal to noise ratio, and visual quality with other inverse halftoning algorithms.
半色调和其他二值图像难以处理，会导致多种降级。如果在缩放、锐化、旋转或其他处理之前将半色调反半色调（转换为灰度），则可以大大减少降级。对于误差扩散半色调，我们提出了（1）一种快速反半色调算法和（2）一种新的多尺度梯度估计器。反半色调算法基于各向异性扩散。它使用新的多尺度梯度估计器在每个像素处改变空间分辨率和灰度分辨率之间的权衡，以获得具有低感知噪声水平的清晰图像。由于算法每个像素需要少于 300 次算术运算，并处理半色调像素的 7x7 邻域，因此非常适合在 VLSI 和嵌入式软件中实现。我们将实现成本、峰值信噪比和视觉质量与其他反半色调算法进行了比较。
