摘要
针对传统的插值算法和基于模型的超分辨算法通常会导致图像对比度和清晰度下降等问题,提出了一种基于泰勒展开式与曲率逆向驱动图像超分辨算法。该算法首先采用泰勒公式估计图像灰度值的变化趋势,然后利用等照度线的曲率细化图像边缘特征,并将梯度作为约束条件抑制图像边缘的锯齿与振铃效应。大量实验表明,所提算法在清晰度和信息保留度上比传统算法更具有优势,算法处理结果更符合人眼视觉效果,在泰勒展开式的基础上进行逆向扩散也使该算法的运行效率明显高于传统迭代算法。
To solve the problem of traditional interpolation and model-based methods usually leading to decrease of the contrast and sharpness of images, a reverse curvature-driven Super-Resolution （SR） algorithm based on Taylor formula was proposed. The algorithm used the Taylor formula to estimate the change trend of image intensity, and then the image edge features were detailed by the curvature of isophote. Gradients were used as constraints to inhibit the jagged edges and ringing effects. The experimental resluts show that the proposed algorithm has obvious advantages over the conventional interpolation algorithm and model-based methods in clarity and information retention, and its result is more in line with human visual effects. The proposed algorithm is more effective than traditional iterative algorithms for reverse diffusion based on Taylor expansion is implemented.
出处
《计算机应用》
CSCD
北大核心
2014年第12期3570-3575,共6页
journal of Computer Applications
基金
国家自然科学基金资助项目(61303127)
国家科技支撑计划项目(2013BAH32F02
2013BAH32F03)
四川省科技厅青年人才培养计划项目(2011JQ0041)
四川省科技厅重点项目(11ZS2009)
四川省教育厅重点项目(11ZA130
13ZA0169)
关键词
图像超分辨
泰勒公式
等照度线
曲率驱动
逆向扩散
image Super-Resolution （SR）
Taylor formula
isophote
curvature-driven
reverse diffusion
