Image Super-resolution using Wavelet Transform and Bicubic Interpolation

This paper entitles the different method available for quality image super-resolution. Nowadays images are widely used over the internet and also in medical and security areas. Interpolation method is used for image superresolution but this method does not give you better results. This paper, proposes an image super-resolution technique based on Bicubic interpolation of high frequency subbands obtained from Discrete Wavelet Transform and the input image. Discrete Wavelet Transform is applied in order to decompose an input image into different subbands. The estimated high frequency subbands are being modified by using high frequency subbands obtained from Stationary Wavelet Transform. All these images are combined to generate new resolution enhanced image by using Inverse Discrete Wavelet Transform which gives you better quality output image. The proposed technique is tested on benchmark images. The quantitative (Peak signal-to-noise ratio) and visual results show the superiority of the proposed technique over conventional and state-of-art image enhancement technique. The PSNR improvement of the proposed technique is up to 5.04dB compared with standard bicubic interpolation.