Sentence examples for missing textures based from inspiring English sources

In this paper, we have presented an adaptive method for reconstructing missing textures based on the SSIM index.

The reconstruction algorithm of the missing textures based on the SSIM index is shown in Section 3.2.

In this approach, the nonconvex maximization problem is reformulated as a quasi convex problem, and adaptive reconstruction of the missing textures based on the perceptually optimized algorithm becomes feasible.

This paper presents a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm.

In this paper, we present a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm.

Next, the missing texture reconstruction method based on the perceptually optimized algorithm is proposed in Section 3. Experimental results that verify the performance of the proposed method are shown in Section 4. Finally, conclusions are given in Section 5.

The proposed method adaptively obtains subspaces utilized for the reconstruction of missing textures by selecting the optimal known local textures based on the SSIM index.

Then the proposed method can adaptively reconstruct the missing textures from only the same kinds of known textures based on the perceptually optimized scheme.

Then the optimal solution based on the SSIM index can be computed, and accurate reconstruction of the missing textures is expected.

Specifically, we introduce the following two novel approaches into the SSIM-based algorithm and realize adaptive reconstruction of missing textures.

In order to reconstruct the missing textures within the target patch from only the same kinds of textures, we have to select those textures from the known areas.