Enhancing the Enlargement of Images Tara Naughton Computer Systems Lab 2009-2010

Introduction Typically two methods of image enlargement Pixel replication Replaces original pixel with group of pixels of the same value Interpolation Replaces original pixel with group of expanded pixels Produce results too jagged or too blurred

Fig 1. Pixel replication vs. interpolation

Similar Research Focus on keeping defined edges Ramp edge model Locate edge pixels, derive parameters, derive intensity, keep parameters the same in the enlarged images Step edge model Divides image into “atomic areas,” derive step edge parameters for each pixel, find intensity of atomic areas, find step-likeness value to see if near step edge, use step-likeness value as weight to combine intensity values derived for atomic area Fig 2. Step edge parameters Fig 3. Ramp edge parameters

Background Coding in Python Takes input of black-and-white .pgm images Outputs enlarged black-and-white .pgm images

Discussion Separates images into parts: edges and non- edges Resize non-edges with interpolation method Find intensity values for edges and resize accordingly

Results Produce images that are neither too blurry nor too jagged Compare between original, resized image, and images resized by other methods Currently produces image resized by pixel replication

Fig 5. Original image Fig 6. Image resized by pixel replication (scaled to smaller size, but with changes to image visible)