Abstract
The drawback of current depth image enhancement algorithms is poor performance of edge preserving. To solve this drawback, the gradient mask guided joint filtering(GMGJF) algorithm is proposed. The Sobel gradient transform is used to obtain the boundary direction information, and the hole region of the depth images was utilized to generate the hole mask.Furthermore, taking the boundary direction and the cavity mask as the guidance, the color image was jointed to perform iterative Gaussian filtering and hole filling on the depth image. Experimental results show that the peak signal to noise ratio(PSNR) and the structural similarity index measure(SSIM) of GMGJF algorithm are improved by at least 3.50% and 1.07% respectively, compared with the iterative median filter(IMF), guided filter (GF) and joint bilateral filter(JBF) algorithms, it has both the strongest ability of denoising and hole filling, and can remain the boundary features best, which is good for feature extraction and target recognition of depth image.
Original language | English |
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Pages (from-to) | 200-206 |
Number of pages | 7 |
Journal | Journal of Applied Optics |
Volume | 39 |
Issue number | 2 |
DOIs | |
Publication status | Published - Mar 2018 |
Keywords
- Depth image
- Gradient mask guided joint filter
- Hole mask
- Image enhancement
- PSNR