基于红黑小波的图像显著性检测  

Image Saliency Detection Using Red-Black Wavelet

作　　者：赵三元[1] 李凤霞[1] 沈建冰[1] 王清云[2] 

机构地区：[1]北京理工大学计算机学院智能信息北京市重点实验室,北京100081 [2]北京仿真中心,北京100854

出　　处：《计算机辅助设计与图形学学报》2014年第10期1789-1793,共5页Journal of Computer-Aided Design & Computer Graphics

摘　　要：频域分析方法是图像显著性检测的经典方法之一,算法简单且计算速度快.然而传统的傅里叶频域分析方法计算出的显著性图精细度较低,难以获得满意的显著性区域分割结果.针对此问题,文中提出基于红黑小波变换的图像显著性检测方法.首先根据图像的尺寸确定红黑小波的分解层数;然后将原始图像和经过高斯平滑处理的图像分别进行红黑小波分解,求得二者分解结果的差值,并对该值进行红黑小波反变换获得显著性图.实验结果表明,与传统的傅里叶频域分析方法相比,该方法可获得更好的显著性检测效果.The spectral residual method is well-known in image saliency detection for its simplicity and low computational cost, although the saliency map of traditional Fourier method is not fine-scaled and cannot offer an ideal detection result. To deal with this problem, we propose a frequency analysis method using red-black wavelet transform to obtain saliency map. The level of wavelet decomposition is determined according to the size of the image. After that the red-black wavelet forward transform is performed on both the original image and its Gaussian smoothing version. The difference between the two decomposition results is inverse transformed in order to obtain the saliency map. The experimental results demonstrate that our method performs a better result in saliency detection.

关 键 词：图像显著性 红黑小波 频域分析 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]