Unsupervised Segmentation of Defocused Video Based on Matting Model
In this paper, an unsupervised segmentation algorithm based on matting model is proposed to extract the focused objects in the low depth of field (DOF) video images. The proposed algorithm is fully automatic and can be used to partition the video image into focused objects and defocused background. This method consists of three stages. The first stage is to generate the saliency map from the input image. In the second stage, bilateral and morphological filtering are employed to smooth and lift the saliency regions. Then a trimap with three regions is calculated by an adaptive thresholding method. The third stage involves the Poisson matting scheme to extract the boundaries of the focused objects accurately. Experimental evaluation on test sequences shows that the proposed method is capable of segmenting the focused region quite effectively and accurately.