Super-Resolution using Combination of Wavelet Transform and Interpolation Based Method

Super-resolution is a technique of producing a high-resolution (HR) image from one or more lowresolution (LR) images. Classical interpolation based magnification techniques like nearest-neighbor, bilinear and bicubic interpolation results in a larger image along with undesirable artifacts like blurring, aliasing and ringing effects. So the aim of super-resolution is to provide a larger image with good quality (quality means an image with less undesirable artifacts). Previous super-resolution techniques are based on using multiple images and learning based methods but the idea here is to use a single image in the super-resolution process. Here we have used the combination of wavelet transform and interpolation based technique to achieve the super-resolution using a single image. First the edges of the image are enhanced using wavelet transform and then the magnification is done using an interpolation based method. A comparison of this algorithm with other technique is also done to provide the quantitative and qualitative result to prove the effectiveness of the methods.