A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from defocus: a spatial domain approach
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Space-variant approaches to recovery of depth from defocused images
Computer Vision and Image Understanding
Recovering Affine Motion and Defocus Blur Simultaneously
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from Defocus vs. Stereo: How Different Really Are They?
International Journal of Computer Vision - Special issue on computer vision research at the Technion
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Depth Measurement by the Multi-Focus Camera
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Comparametric equations with practical applications in quantigraphic image processing
IEEE Transactions on Image Processing
Hi-index | 0.10 |
Depth-from-defocus (DFD) is useful in 3-D range image acquisition and automatic focusing. However, DFD needs precise calibration of internal camera parameters. Most DFD techniques use well known camera calibration techniques or specially designed vision systems to precisely measure the settings of the lens system of a camera. In this paper, we introduce an image-based defocus calibration technique. Especially we employ the Spatial domain Convolution/Deconvolution Transform Method (STM) which is introduced by Subbarao and Surya [Subbarao, M., Surya, G., 1994. Depth-from-defocus: A spatial domain approach. Internat. J. Comput. Vision 13 (3), 271-294]. STM estimates blur parameters @s"1 and @s"2 of defocused images obtained at two different lens steps of the camera. In STM, the blur difference between two defocused images is considered to be a constant value which is determined by internal camera parameters. We use the blur level of the defocused images to calibrate blur difference and camera parameters. Calibrated parameters yield consistent results in depth estimation. Experimental results of depth measurement using real objects are presented.