摘要
智能手机等移动设备受电池续航及计算能力的限制,在面向图像/视频处理应用时需要进行特定的算法设计和优化.为此提出一种快速的非局部均值图像去噪算法.首先利用像素点权值计算的对称性原理减少像素权值的计算量;然后根据实验确定的优化步长对图像进行下采样,并利用权重公式和双线性插值算法分别对采样点和非采样点的权值进行计算;最后应用NEON指令对部分C语言代码进行汇编级优化.实验结果表明,与传统非局部均值图像去噪算法相比,该算法在轻微图像质量损失的情况下大幅减少了图像的去噪时间,能够满足手机等移动终端上的实时图像处理要求.
Mobile devices, such as smart phones, are constrained to the image/video processing capacity due to their limited battery life and computational power. In order to cope with these bottlenecks, in this paper, we propose a novel fast non-local means image denoising technique for mobile image processing. The major steps of the proposed technique includes： we reduce the computation of pixels utilizing the symmetry of pixel weights; in the sampling optimization step, certain pixels are selected and their weights are computed by the weighted formula while the weights of the unselected pixels are computed by the bilinear interpolation method; we optimize the codes of the program with NEON instructions in the assembly level. The experiments show that： the image denoising time of the proposed technique is reduced effectively compared to the traditional non-local means image denoising technique with little image quality loss, which satisfies the real-time requirement on mobile devices.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2016年第8期1260-1268,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(61202207
61379079
61472370
61502433)
国家科技支撑计划(2013BAH23F01)
中国博士后基金(2015M582203)
关键词
图像去噪
非局部均值
下采样
欧氏距离
移动设备
image denoising
non-local means
subsample
Euclidean distance
mobile equipment
