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

This study explores methods of image enlargement, specifically pixel replication and interpolation, and proposes an algorithm that combines edge detection and interpolation to produce enhanced results. The algorithm is implemented in Python and tested on black-and-white PGM images.

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

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

  2. 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

  3. Fig 1. Pixel replication vs. interpolation

  4. Fig 2. Original image Fig 3. Zoom by pixel replication Fig 4. Zoom by interpolation

  5. 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 5. Step edge parameters Fig 6. Ramp edge parameters

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

  7. .pgm images • Portable graymap format • Gray-scale image Explains the type of file (P2 for PGM) Width and length of image Range of intensity values Intensity Values of pixels

  8. Discussion • Separates images into parts: edges and non-edges • Resize non-edges with interpolation method • Find intensity values for edges and resize accordingly • Equation that takes multiple variables into account, including edge value • Produce images neither too blurred or too jagged • Compare between original, resized image, and image resized by other methods

  9. Results • Pixel replication and interpolation methods completed • Algorithm to identify edges completed • Complete interpolation algorithm including isolation of edges being toyed with

  10. Fig 7. Original image Fig 8. Image resized by pixel replication

  11. Fig 9. Image resized by interpolation Fig 10. Edges of interpolated image

  12. Future Research • Algorithm could be developed further to improve quality • Work with color images and other file types

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