Depth Image Vibration Filtering and Shadow Detection Based on Fusion and Fractional Differential
Ting Cao, Pengjia Tu, Weixing Wang · International Journal of Pattern Recognition and Artificial Intelligence · 2020
The depth image generated by Kinect sensor always contains vibration and shadow noises which limit the related usage. In this research, a method based on image fusion and fractional differential is proposed for the vibration filtering and shadow detection. First, an image fusion method based on pixel level is put forward to filter the vibration noises. This method can achieve the best quality of every pixel according to the depth images sequence. Second, an improved operator based on fractional differential is studied to extract the shadow noises, which can enhance the boundaries of shadow regions significantly to accomplish the shadow detection effectively. Finally, a comparison is made with other traditional and state-of-the-art methods and our experimental results indicate that the proposed method can filter out the vibration and shadow noises effectively based on the [Formula: see text]-measure system.