In order to effectively recover the occlusion

this paper presents an iterative quadratic programming method for occlusion recovery. Based on the characteristic that the projections of the row vector and the column vector of image matrix to the orthogonal complementary subspace spanned by image matrix are zero vectors

the row and the column residual objective functions are respectively defined. At the same time

the occlusion positions are respectively sorted according to the row and the column order

whichcan be denoted by a transformation matrix. Based on the transformation matrix

a united residual objective function which is quadratic is obtained from the row and the column ones. The method has the advantages that both the row and the column constraints are simultaneously considered and the solution of occlusion is transformed to iterative solution a quadratic programming. The experimental results show that the method has fast convergence speed and high precision.