Several factors can interfere in the quality of image such as aliasing, noise, artifact, and blurring, these factors can cause the degradation of image especially in edge regions. In order to reduce the effect of these factors, it is necessary to choose a robust interpolation method which can play important role of the reconstruction of the high-resolution image from its low-resolution counterpart, so as to preserving the edges and textures, increasing the resolution, and improving the image quality.
In this paper, a new image interpolation method is proposed using gradient orientation; in the first step, we estimate the edges directions for a missing pixel location using the gradient-orientation in horizontal and vertical directions. Then, in the second step we interpolate the missing pixels along the detected edge directions using a cubic spline interpolation.
We begin from a gray high-resolution image which is down-sampled by a factor of two, to obtain the low-resolution image, then; this image is reconstructed using the proposed algorithm. Our method is implemented and tested to several gray test images, and compared to other image interpolation methods. The simulation results show the effectiveness of the proposed technique using the PSNR and compared with the traditional interpolation techniques. The results showed that the proposed technique has higher accuracy, and can preserve the sharp edges and textures, and avoid the problems of blurring and the visual artifacts caused by the classical interpolation methods.