Image super resolution scheme based on wavelet transform and its performance analysis

Super resolution is very useful and interesting area of research in image processing applications based on wavelet transform. Many algorithms have been developed by researchers based on Projection Onto Convex Set (POCS), Maximum-aposteriori (MAP) and Maximum Likelihood (ML). In this paper, we propose super resolution algorithm based on Stationary Wavelet Transform (SWT) and Discrete Wavelet Transform (DWT). Single frame super resolution can be achieved by use of different interpolation method but this scheme generates blur at the edges of images. Hence in this paper we relied on wavelet transform for super resolution algorithm with different orthogonal and bi-orthogonal filters. Quality aspect of image such as MSE, PSNR, SSIM and Correlation Coefficient are calculated with this proposed algorithm.