在Weber定律的启发下提出一种基于 "恰可识别差异"的尺度空间自适应构建方法。Weber定律认为人类感知模式不仅与刺激的变化有关,而且与原刺激强度有关。基于此观点,在图像尺度空间的构建过程中,首先以Marr视觉理论的屋脊型边缘和阶梯型边缘的特征之和计算图像的信息量,再通过实验获得人类视觉能感知到"恰可识别差异"时的图像信息量变化,最后通过曲线拟合自适应构建图像的尺度空间。实验结果表明,该方法充分体现了人类视觉感知特性,与其他尺度空间构建方法相比,在目标匹配实验中,匹配数目提升了25%以上;在去噪实验中,本算法的去噪效果良好。

Inspired by Weber’s Law,we propose an adaptive method to build up scale-space based on "just noticeable difference". This is because human perception of patterns depend not only on the change of a stimulus but also on the original intensity of the stimulus. According to this point of view,we use the ramp edge and step edge to calculate the image information amount based on Marr’s theory. The information lost between the adjacent scale layers is then gained in experiments when the human vision can feel the "just noticeable difference" . Finally,the scale-space is constructed adaptively by curve fitting method. The experimental results show that the algorithm can exhibit the characteristics of human visual perception. In the matching experiments,the number of matched points can be increased at least by 25% by the adaptive algorithm and it impressively outperforms the other scale-space construction method in denoising field.