一种改进的各向异性扩散深度图像增强算法

深度图像受其测距原理所限,存在边缘不匹配、无效像素、噪声等问题,提出一种基于改进的各向异性扩散算法的深度图像增强方法。首先,校正深度图像和彩色图像的位置关系,并根据时间连续性选择多帧图像,进行多帧均值滤波预处理;其次,通过在彩色图像中引入权重的思想,构建具有4-邻域形式的深度图像模型,利用彩色图像引导的深度图像进行各向异性扩散,填补孔洞;最后,使用改进的自适应中值滤波平滑图像噪声。实验结果表明,该方法能够有效修复原始深度图像中存在的由无效像素组成的黑色孔洞,在抑制噪声的同时,仍能保持深度图像中物体边缘的细节信息。

A depth image enhancement algorithm basedon improved anisotropic diffusion

Depth images have some problems such as edge mismatching, invalid pixels and noise, which are induced by the measuring distance principle. We present a depth image enhancement method based on the improved anisotropic diffusion algorithm. Firstly, we correct the position relationship between the depth image and the color image, and choose more frames to preprocess the multi-frame mean filtering according to the time continuity. Secondly, we build a depth image model with 4-neighborhood by introducing the idea of weights to the color image. The anisotropic diffusion is conducted on the depth image under color image guidance and the holes are filled. Finally, we use the improved adaptive median filtering smooth algorithm to remove image noise. Experimental results show that the proposed method can effectively repair the black holes composed of invalid pixels in the original depth image and remain the detailed information of the object’s edge in the depth image while suppressing the noise.