The accumulation buffer: hardware support for high-quality rendering
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
A lens and aperture camera model for synthetic image generation
SIGGRAPH '81 Proceedings of the 8th annual conference on Computer graphics and interactive techniques
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ACM SIGGRAPH 2005 Papers
Iterative Kernel Principal Component Analysis for Image Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
A phenomenological model for bokeh rendering
ACM SIGGRAPH 2002 conference abstracts and applications
Active refocusing of images and videos
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2007 papers
Focused image recovery from two defocused images recorded with different camera settings
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
We present a system that allows for changing the major camera parameters after the acquisition of an image. Using the high dynamic range composition technique and additional range information captured with a small and low-cost time-of-flight camera, our setup enables us to set the main parameters of a virtual camera system and to compute the resulting image. Hence, the aperture size and shape, exposure time, as well as the focus can be changed in a postprocessing step. Since the depth-of-field computation is sensitive to proper range data, it is essential to process the color and depth data in an integrated manner. We use a non-local filtering approach to denoise and upsample the range data. The same technique is used to infer missing information regarding depth and color which occur due to the parallax between both cameras as well as due to the lens camera model that we use to simulate the depth of field in a physically correct way.