Di Zang

Publications (2)6.99 Total impact

• Article: Robust disparity estimation based on color monogenic curvature phase.

  Di Zang, Jie Li, Dongdong Zhang, Junqi Zhang
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  ABSTRACT: Disparity estimation for binocular images is an important problem for many visual tasks such as 3D environment reconstruction, digital hologram, virtual reality, robot navigation, etc. Conventional approaches are based on brightness constancy assumption to establish spatial correspondences between a pair of images. However, in the presence of large illumination variation and serious noisy contamination, conventional approaches fail to generate accurate disparity maps. To have robust disparity estimation in these situations, we first propose a model - color monogenic curvature phase to describe local features of color images by embedding the monogenic curvature signal into the quaternion representation. Then a multiscale framework to estimate disparities is proposed by coupling the advantages of the color monogenic curvature phase and mutual information. Both indoor and outdoor images with large brightness variation are used in the experiments, and the results demonstrate that our approach can achieve a good performance even in the conditions of large illumination change and serious noisy contamination.
  Optics Express 07/2012; 20(14):14971-9. · 3.59 Impact Factor
• Article: Robust visual correspondence computation using monogenic curvature phase based mutual information.

  Di Zang, Jie Li, Dongdong Zhang
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  ABSTRACT: Visual correspondence has been a major research topic in the fields of image registration, 3D reconstruction, and object tracking for some decades. However, due to the radiometric variations of images, conventional approaches fail to produce robust matching results. The traditional method of intensity-based mutual information performs very good for global variations between images, however, its performance degrades in the case of local radiometric variations. Monogenic curvature phase information, as an important local feature of the image, has the advantage of being robust against brightness variation. Hence, in this Letter, we propose an approach to compute the visual correspondence by coupling the advantages of mutual information and monogenic curvature phase. Experimental results demonstrate that the proposed approach can work robustly under radiometric variations.
  Optics Letters 01/2012; 37(1):10-2. · 3.40 Impact Factor