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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：在超分辨率算法中，插值任务在高分辨率图像质量重建中起着关键作用。事实上，经典插值算法遇到的最大缺点是，当用于消除输入图像中的模糊和噪声时，它们往往效果不佳。从这个意义上说，这项工作的目的是开发一种插值方案，以减少输入图像中的这些伪影，从而保持边缘的清晰度。该方法基于图像插值，首先使用拉普拉斯算子估计边缘方向，然后使用三次卷积插值从强边缘插值缺失像素。我们从一幅灰度高分辨率图像开始，将其下采样两倍，以获得低分辨率图像，然后使用所提出的插值算法进行重建。利用几种灰度图像对该方法进行了实现和测试，并与其他插值方法进行了比较。仿真结果表明，除了重建图像的视觉质量外，该方法在PSNR、SSIM和FSIM两个感知质量指标上都优于其他图像插值方法。

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