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The application of Laplacian pyramid in image super-resolution reconstruction

Image super-resolution reconstruction is a process that obtaining high resolution images from low-resolution degraded images. In frequency domain, it is a process to obtain the detail. The Laplacian pyramid model is proposed to simulate the degraded course, and the approximation signal of the Laplacian pyramid decomposition is considered to be the degraded image, so the process of super-resolution reconstruction is the process of Laplacian pyramid reconstruction without the detail image. Since the degraded course is very complex, the analysis just discusses the degraded images caused by the high frequencies components are attenuated by the averaging process in the digital image acquisition process. Experimental results show the proposed approach can effectively improve the image quality both objectively (PSNR) and subjectively.