Publication: Image super resolution using interpolation
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Date
2009-04-01
Authors
Lee, Siang Hoe
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Abstract
Interpolation is a method to enlarge an image. It collects information from an image and uses this information to predict the unknown information in the upgrade size of image. The information in an image will affect the image resolution. Low resolution image has least information or smaller image size, and high resolution image has more information and bigger image size. In this project, a low resolution image is interpolated by four different interpolation methods, and this interpolated image is filtered by four filtering methods. These four interpolation and four filtering methods are nearest neighbor interpolation, bilinear interpolation, bicubic interpolation, Lanczos interpolation, smoothing filter, Gaussian filter, sharpening filter and unsharp masking filter. The final image of each method is compared, and the difference with ground truth image is measured. Based on the results, it shows that magnification ratio is inversely proportional to output image. As magnification ratio increase, the output image quality is decreased. In up sampling an image, interpolation methods should be considered first then only filtering methods. This because interpolation methods affects output result the most rather than filtering methods. Bicubic interpolation gives 18.5513 of MSE value and Gaussian filter gives 17.3515 of MSE value which both are the lowest MSE value among others interpolation and filtering methods for magnification factor of two.