【摘要】 提出了一种自适应的双向耦合扩散算法:沿着等照度线(边缘)的梯度方向实施反向扩散以增强边缘,而相反地沿切线方向实施正向扩散以去除人工锯齿。为了消除这2个相反的扩散力彼此之间的冲突,将此算法分裂为一种耦合的格式;同时,为了保持图像特征,利用图像的方向导数局部地调整非线性扩散系数。最后将上述算法应用于图像插值。实验结果显示,相比于传统的图像插值算法和一些相关的偏微分方程模型,此图像插值算法可以显著地提高被插值图像的视觉质量。更多还原

【Abstract】 An adaptive coupled bidirectional flow process was presenfed,where an inverse diffusion was performed to enhance edges along the normal directions to the isophote lines(edges),while a normal diffusion was done to remove ar-tifacts(“jaggies”) along the tangent directions.The two converse diffusion forces were splitted into a coupled form to stop the cancellation between each other.In order to preserve image features,the nonlinear diffusion coefficients were locally adjusted according to the directional derivatives of the image.And then the above process was applied to image interpolation.Experimental results demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations and relative equations.更多还原