| Summary: | 3D video systems provide a sense of depth by showing slightly different images to the viewer’s left and right eyes. 3D video is usually generated by capturing a scene with two or more cameras and 3D displays need to be able to concurrently display at least two different images. The use of multiple cameras and multiple display channels creates problems that are not present in 2D video systems. At the capturing side, there can be inconsistencies in the videos captured with the different cameras, for example the videos may differ in brightness, colour, sharpness, etc. At the display side, crosstalk is a major problem. Crosstalk is an effect where there is incomplete separation of the images intended for the two eyes; so the left eye sees a portion of the image intended for the right eye and vice versa. In this thesis, we develop methods for correcting these capturing and display distortions in 3D video systems through new digital video processing algorithms.
First we propose a new method for correcting the colour of multiview video sets. Our method modifies the colour of all the input videos to match the average colour of the original set of views. Experiments show that applying our method greatly improves the efficiency of multiview video coding. We present a modification of our colour correction algorithm which also corrects vignetting (darkening of an image near its corners), which is useful when images are stitched together into a panorama.
Next, we present a method for making stereo images match in sharpness based on scaling the discrete cosine transforms coefficients of the images. Experiments show that our method can greatly increase the accuracy of depth maps estimated from two images that differ in sharpness, which is useful in 3D systems that use view rendering.
Finally, we present a new algorithm for crosstalk compensation in 3D displays. Our algorithm selectively adds local patches of light to regions that suffer from visible crosstalk, while considering temporal consistency to prevent flickering. Results show our method greatly reduces the appearance of crosstalk, while preserving image contrast.
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