This study presents a hybrid technique for simultaneously completing images by using geometry and texture components of input data. The approaches using inpainting methods based on partial differential equations (PDEs) to fill in large image regions usually fail if these regions contain textures. On the other hand, texture synthesis algorithms sometimes fail due to complex structures and textures in the image. However, this study, suggesting a hybrid method using both techniques, produces satisfactory results in completing the missing parts of images. In the proposed method, the given image is decomposed into two components. The geometry component, obtained by using the regularization PDE based on a trace operator, was inpainted by a tensor-driven PDE algorithm that takes curvatures of line integral curves into account, and the texture component, obtained by subtracting the given image from the geometry component, was reconstructed by the modified exemplar-based inpainting algorithm. Both of these methods work on color information. The main contribution of this paper is that it uses decomposition and montage stages together which provides superior results compared with the existing methods. Experimental results show that the proposed method efficiently fills in target regions, which is promising.