Analysis of Medical Image Resizing Using Bicubic Interpolation Algorithm

Image interpolation is the most basic requirement for many image processing tasks such as medical processing. a technique used in resizing an image. To change size, each pixel new must be remapped to location old calculate value. There are algorithms available determining value, of which involve some form between closest pixels In this paper, we use Bicubic algorithm size images from Messidor dataset and then analyze it by measuring using three parameters Mean Square Error (MSE), Root Squared (RMSE), Peak Signal-to-Noise Ratio (PSNR), compare results with Bilinear Nearest-neighbor algorithms. The showed that better than larger dimensions resized, higher degree similarity original image, but level computation complexity also increases.