Performance Evaluation of Edge Directional Image Interpolation Scheme

Earlier there are different interpolation techniques for denoising of images. When an image is zoomed checkerboard effect/ringing arises in images. In order to remove interpolation artefacts such as image blur and checkerboard effect. The proposed technique “DIRETIONAL DENOISE SCHEME” tries to amend the interpolation error. Meanwhile edge preservation is a critical issue in both image denoising and interpolation. In this project, we are using directional denoising scheme interpolation method to address the edge preservation. Linear interpolation methods have been introduced without considering specific local information on edges results in to artefacts. Non linear interpolation methods have been suggested to reduce the artefacts of linear method. These nonlinear methods are often computation intensive and they can be more expensive than linear methods for 2DImages.Further, they become inefficient in the estimation of edge orientation for the classes of edge model with fine scales. More effective interpolation methods are yet to be developed in order to accurately preserve the edge orientation without introducing high computational cost. Peak Signal to Noise Ratio (PSNR) Normalized Cross Correlation (NCC) and CPU Run time are used as quantitative measures to compare the ground truth image with zoomed interpolated images. The new interpolation scheme is expected to result in high resolution images having clearer and sharper edges over existing linear interpolation methods.