摘要
在应用经典小波检测图像边缘时,通常利用离散积分替代连续积分获取小波系数。由于离散积分仅仅是连续积分的近似表达,因此这种方法在获取图像边缘时很难避免数值计算误差,这使得在检测图像细节部分时容易出现定位不准和边缘不清晰等问题。为了避免上述问题,利用插值小波采样理论中像素值即为插值小波系数的特殊性质,将插值共轭滤波器与Mallat塔式分解算法相结合,给出一种新的图像边缘检测算法。将该算法与经典小波算法进行对比实验,结果表明,该方法能够检测出经典小波算法无法检测到的边缘细节,且最终得到的图像边缘清晰完整,从而验证了该算法的有效性。
When classic wavelet theory is applied to detect edge of images,discrete integral formula is often used to replace continuous integral to obtain wavelet coefficients.Since discrete integral is approximate expression of continuous integral,great numerical errors often cannot be avoided in calculations.This has lead to the fact that some details of images cannot be described clearly in edge detection.To solve this problem,by applying Mallat pyramidal algorithm to interpolation conjugate filter,a new algorithm was proposed for edge detection based on the fact that image pixel values can be considered as coefficients of interpolation wavelets.In the experiment,our algorithm is compared with the classic one.It is shown that the new algorithm can obtain clearer and more intact edges.This implies that our algorithm is more effective and accurate than the classic one.
出处
《计算机科学》
CSCD
北大核心
2017年第S1期164-168,共5页
Computer Science
基金
国家自然科学基金项目(60904072
71301018)
教育部留学回国人员科研启动基金(M16010701LXHG5008)
中央高校基本科研业务费专项资金(ZYGX2015J078)资助
关键词
插值小波
插值共轭滤波器
塔式分解
图像边缘检测
Interpolation wavelet
Interpolation conjugate filter
Mallat pyramidal
Image edge detection
