To solve the spatially varying out of focus deblurring problem of a conventional camera, a spatially varying out of focus deblurring approach based on blur map and L1 2 optimization is proposed. Firstly, the defocusing model of camera is studied and analyzed, and the principle, characteristics and applicability of circular defocusing model and Gaussian defocusing model are presented. And then, the local contrast prior condition is modified using the edge properties, the blur map is obtained in combination with the gradient information of fuzzy edge, and a guided filtering method is adopted to remove the ambiguity around edges and the noise of blur map, thus obtain a better blur map. Finally, L1 2 optimization that combines Tikhonov like regularization and TV regularization is applied to image deburring, which is accomplished with variable splitting and punishment method, and the all in focus image is obtained using scale selection and image reconstruction. The experimental results based on both synthetic image and real image show that the proposed approach outperforms the state of the art space invariant and spatially varying deblurring methods.