2D-to-3D conversion is a feasible solution to the problem of 3D-content deficiency.In the conversion

depth extraction from a single 2D image is the key step.We propose a depth estimation method based on edge-gradients ratio and object-guided energy model.First

we obtain two blurred images from the input defocused image via Gaussian smoothing using two different kernels.Then

we estimate the sparse depth map generated from the gradients ratio at edge locations in the two blurred images.Next

we recover the full depth map from the sparse depth map by matting Laplacian interpolation.Objects are then extracted from the input image by adaptive threshold binary segmentation on its visual saliency map.Finally

the refined depth map is obtained through object-guided depth filtering.Synthetic and real images experimental results both show that our algorithm is superior to the existing methods.