Fast 2D to 3D conversion based on wavelet analysis

This paper proposes a depth estimation method which converts two-dimensional images of limited depth of field (DOF) into three-dimensional data. The goal is to separate the focused foreground objects from the blurred background objects in an image. Our approach is based on two observations: (1) the focused objects on an image of limited DOF correspond to the objects with high frequency; (2) the high-frequency area of an image appears high energy on its high-frequency wavelet subbands. In our approach, each image is first transformed to the YUV color space; then Y component of the image is further transformed to the wavelet domain. Afterwards, the high-frequency area of an image can be obtained from analyzing the high-frequency wavelet subbands of the image. Finally, binarization and smoothing techniques are applied to find the position of the focused objects on the image. The experimental result demonstrates the effectiveness of our approach.