As to extract better texture from an infrared polarization image, variational decomposition has a good effect which extracts texture in the premise of energy index. First this paper introduces description of infrared polarization image in Stokes vector and hierarchical variational decomposition (BV, G<sub>p</sub>, L<sup>2</sup>) model. And we use this model method for multiscale texture extraction of the infrared polarization image. A given infrared polarization image is decomposed into the characteristics of the three different components of u, v, r through the minimization of the energy functional. In this decomposition, v represents the fixed scale texture of f , which is measured by the parameter λ. To achieve a multiscale representation, we proceed to capture essential textures of f which have been absorbed by the residuals. Then we make energy as an index of the texture evaluation. The experiments show that the algorithm is effective to extract better texture from an infrared polarization image.