Disparity map enhancement in pixel based stereo matching method using distance transform
| Autor: | Yong-Jun Chang, Yo-Sung Ho |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Pixel
Computer science business.industry Computation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Stereo matching 020206 networking & telecommunications Pattern recognition 02 engineering and technology Image (mathematics) Signal Processing Content (measure theory) 0202 electrical engineering electronic engineering information engineering Media Technology Binocular disparity 020201 artificial intelligence & image processing Computer vision Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering Error detection and correction business Distance transform |
| Zdroj: | Journal of Visual Communication and Image Representation. 40:118-127 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2016.06.017 |
| Popis: | The pixel based cost computation using the distance transform is proposed.The distance transform gives specific values to the pixel in the textureless region.The stereo matching based on the distance transform outperforms in the result image comparing with the conventional method.The disparity error detection and correction methods are also proposed as a post-processing step to enhance the result image. With the great success in three-dimensional (3D) movies, a lot of 3D content have been generated. Depth information is one of the important elements in 3D content generation. Stereo matching methods obtain depth information using the characteristic of binocular disparity. These methods find corresponding points between two images which have different viewpoints to calculate the disparity value. However, these methods have difficulties computing accurate disparity values in the textureless region. Smeared pixels near the edge region also make difficult for the stereo matching. In this paper, we propose a pixel based cost computation for the cross-scale stereo matching using the distance transform to improve these problems. In addition, the disparity error detection and correction methods are also proposed as a post-processing step. As a result, we obtain the enhanced disparity map which is robust to the textureless region and the edge region. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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