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首页> 外文期刊>WSEAS Transactions on Signal Processing >A new directional image interpolation based on Laplacian operator
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A new directional image interpolation based on Laplacian operator

机译：基于拉普拉斯算子的新方向性图像插值

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摘要

The interpolation task plays a key role in the reconstruction of high-resolution image quality in super-resolution algorithms. In fact, the foremost shortcoming encountered in the classical interpolation algorithms, is that they often work poorly when used to eliminate blur and noise in the input image. In this sense, the aim of this work is to develop an interpolation scheme for the purpose of reducing these artifacts in the input image, and consequently preserve the sharpness of the edges. The proposed method is based on the image interpolation, and it is started by the estimation of the edges directions using the Laplacian operator, and then interpolated the missing pixels from the strong edge by using the cubic convolution interpolation. We begin from a gray high-resolution image that is down-sampled by a factor of two, to obtain the low-resolution image, and then reconstructed using the proposed interpolation algorithm. The method is implemented and tested using several gray images and compared to other interpolation methods. Simulation results show the performance of the proposed method over the other methods of image interpolation in both PSNR, and two perceptual quality metrics SSIM, FSIM in addition to visual quality of the reconstructed images results.
机译：插值任务在超分辨率算法中重建高分辨率图像质量的重构中起关键作用。事实上，经典插值算法中遇到的最重要的缺点是它们通常在用于消除输入图像中的模糊和噪声时常常工作。从这个意义上讲，这项工作的目的是开发一个插值方案，以减少输入图像中的这些伪像，因此保持边缘的锐度。所提出的方法基于图像插值，并且通过使用拉普拉斯操作员估计边缘方向来开始，然后通过使用立方卷积插值来插入来自强边的缺失像素。我们从灰度高分辨率图像开始，该图像被缩小为两个，以获得低分辨率图像，然后使用所提出的插值算法重建。使用几个灰度图像实现和测试该方法，并与其他插值方法进行比较。仿真结果表明，除了重建的图像结果的视觉质量之外，PSNR中的图像插值和两个感知质量度量SSIM的其他方法的性能。

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