Resolution Enhancement Using Frequency Domain Interpolation

In various fields of digital signal processing and image analysis, the need to enhance the resolution of low-quality or under sampled data is a common challenge. This abstract introduces a novel approach to resolution enhancement, utilizing Frequency Domain Interpolation (FDI) techniques. Resolution enhancement is a fundamental requirement in applications such as medical imaging, remote sensing, surveillance, and computer vision. Traditional interpolation methods, like bilinear or bicubic, often lead to undesirable artifacts and limited improvements in image quality, particularly when significant upscaling is required. The proposed approach leverages the frequency domain as an alternative to spatial domain techniques, offering advantages such as reduced aliasing and superior preservation of image details. By exploiting the rich spectral information present in the input data, FDI aims to provide more accurate and visually pleasing high-resolution reconstructions. We do the experiment on 128x128 ,512x512 images using nearest neighbour, bicubic ,bilinear interpolation and wavelet method.