一种基于分形码和模型约束的图像放大算法

图像放大技术在众多研究领域中有着重要的应用.本文提出一种基于分形码和模型约束的图像放大算法,分形码能够包含图像的空间信息和图像本身的自相似信息,模型约束能够有效的限制放大引入的误差.我们首先对图像采用多种值域块分割方案计算得到多组分形码,并由此得到多个放大图像,然后对放大图像进行平均,从而降低编码误差,最后采用约束模型对放大图像进行修正.实验结果表明,利用本文的方法可以大大提高放大图像的PSNR.

Image Magnification Based on Fractal Codes and Model Constraint

Image magnification plays an important role in many fields. An algorithm based on fractal codes and model constraint is proposed in this paper. The fractal codes can carry the spatial information as well as the self-similarities present in the image. First,the image is magnified with multiple range block partition schemes,then their results are averaged to get one magnification image and thus the block artifact is reduced. Finally, the magnification image is modified by a constrained model. Experiments show that the proposed approach performs better than the other fractal based magnification method.