Super Resolution Image Generation Using Wavelet Domain Inter Polation with Edge Extraction Via A Sparse Representation

This letter addresses the problem of generating a super-resolution (SR) image from a single lowresolution (LR) input image in the wavelet domain. To achieve a sharper image, an intermediate stage for estimating the highfrequency (HF) sub bands has been proposed. This stage includes an edge preservation procedure and mutual interpolation between the input LR image and the HF sub band images, as performed via the discrete wavelet transform (DWT). Sparse mixing weights are calculated over blocks of coefficients in an image, which provides a sparse signal representation in the LR image. The entire sub band images are used to generate the new high-resolution image using the inverse DWT. Experimental results indicated that the proposed approach outperforms existing methods in terms of resolution This stage includes an edge preservation procedure and mutual interpolation between the input LR image and the HF sub band images, as performed via the discrete wavelet transform (DWT). Sparse mixing weights are calculated over blocks of coefficients in an image, which provides a sparse signal representation in the LR image. All of the sub band images aroused to generate the new high-resolution image using the inversed. Experimental results indicated that the proposed approach outperforms existing methods in terms of objective criteria and subjective perception improving the image resolution