Depth Image Enhancement and Detection on NSCT and Fractional Differential

被引:11
作者
Cao, Ting [1 ]
Wang, Weixing [1 ]
机构
[1] Changan Univ, Sch Informat Engn, Xian, Shaanxi, Peoples R China
关键词
Kinect sensor; Depth image; NSCT; Retinex; Fractional differential;
D O I
10.1007/s11277-018-5494-y
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
For enhancing the low contrast and detecting the noise in depth image from Kinect sensor, the Non-Subsampled Contourlet Transform (NSCT) and non-linear fractional differential are studied in this paper. Firstly, on the basis of the NSCT's advantages, the depth image is decomposed into low frequency and high frequency. The low frequency component is applied to enhance depth image using adaptive scale Retinex, and the scale parameter is adjusted by local mean and standard deviation. The high frequency component is calculated by Non-Local-Means operator to preserve the texture detail. The final enhanced image can be achieved by inverse NSCT. Secondly, the fractional differential theory is studied to accomplish noise detection. The experimental results show that the proposed method can enhance the depth image and detect noise effectively.
引用
收藏
页码:1025 / 1035
页数:11
相关论文
共 13 条
[1]  
[Anonymous], 2010, PROC CVPR IEEE, DOI DOI 10.1109/CVPR.2010.5539965
[2]   3D shape descriptor for object recognition based on Kinect-like depth image [J].
As'ari, M. A. ;
Sheikh, U. U. ;
Supriyanto, E. .
IMAGE AND VISION COMPUTING, 2014, 32 (04) :260-269
[3]   On the use of Kinect depth data for identity, gender and ethnicity classification from facial images [J].
Boutellaa, Elhocine ;
Hadid, Abdenour ;
Bengherabi, Messaoud ;
Ait-Aoudia, Samy .
PATTERN RECOGNITION LETTERS, 2015, 68 :270-277
[4]  
Centeno JAS, 1997, PATTERN RECOGN, V30, P1183, DOI 10.1016/S0031-3203(96)00145-8
[5]  
Fanelli G., 2011, IEEE Conf. Comput. Vision and Pattern Recogn, P617
[6]  
Khan A, 2012, LECT NOTES COMPUT SC, V7383, P588, DOI 10.1007/978-3-642-31534-3_86
[7]   Image denoising and enhancement based on adaptive fractional calculus of small probability strategy [J].
Li, Bo ;
Xie, Wei .
NEUROCOMPUTING, 2016, 175 :704-714
[8]   Adaptive fractional differential approach and its application to medical image enhancement [J].
Li, Bo ;
Xie, Wei .
COMPUTERS & ELECTRICAL ENGINEERING, 2015, 45 :324-335
[9]   A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking [J].
Liu, Lu ;
Jia, Zhenhong ;
Yang, Jie ;
Kasabov, Nikola .
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2015, 25 (03) :199-205
[10]   Obstacle detection in a greenhouse environment using the Kinect sensor [J].
Nissimov, Sharon ;
Goldberger, Jacob ;
Alchanatis, Victor .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2015, 113 :104-115