Example-Based Super-Resolution William T. Freeman, Thouis R. Jones, and Egon C. Pasztor MERL, Mitsubishi Electric Research Labs. 201 Broadway Cambridge, MA 02139 TR-2001-30 August 2001 Abstract Image-based models for computer graphics lack resolution independence: they cannot be zoomed much beyond the pixel resolution they were sampled at without a degradation of quality. Interpolating images usually results in a blurring of edges and image details. We describe image interpolation algorithms which use a database of training images to create plausible high-frequency details in zoomed images. Image pre-processing steps allow the use of image detail from regions of the training images which may look quite different from the image to be processed. These methods preserve fine details, such as edges, generate believable textures, and can give good results even after zooming multiple octaves. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. Copyright © Mitsubishi Electric Information Technology Center America, 2001 201 Broadway, Cambridge, Massachusetts 02139* Egon Pasztor’s present address: MIT Media Lab 20 Ames St. Cambridge, MA 02139 William T. Freeman, Thouis R. Jones, Egon C. Pasztor Mitsubishi Electric Research Laboratories (MERL) 201 Broadway Cambridge, MA 02139 Abstract Image-based models for computer graphics lack resolution independence: they cannot be zoomed much beyond the pixel resolution they were sampled at without a degradation of quality. Interpolating images usually results in a blurring of edges and image details. We describe image interpolation algorithms which use a database of training images to create plausible high-frequency details in zoomed images. Image pre-processing steps allow the use of image detail from regions of the training images which may look quite different from the image to be processed. These methods preserve fine details, such as edges, generate believable textures, and can give good results even after zooming multiple octaves. 1 Introduction As shown in Fig. 1, polygon-based representations of 3-dimensional objects offer resolution independence over a wide range of scales. Object boundaries remain sharp as one zooms in on the object until very close range, where faceting appears due to finite polygonExample-Based Super-Resolution William T. Freeman, Thouis R. Jones, and Egon C. Pasztor MERL, Mitsubishi Electric Research Labs. 201 Broadway Cambridge, MA 02139 TR-2001-30 August 2001 Abstract Image-based models for computer graphics lack resolution independence: they cannot be zoomed much beyond the pixel resolution they were sampled at without a degradation of quality. Interpolating images usually results in a blurring of edges and image details. We describe image interpolation algorithms which use a database of training images to create plausible high-frequency details in zoomed images. Image pre-processing steps allow the use of image detail from regions of the training images which may look quite different from the image to be processed. These methods preserve fine details, such as edges, generate believable textures, and can give good results even after zooming multiple octaves. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. Copyright © Mitsubishi Electric Information Technology Center America, 2001 201 Broadway, Cambridge, Massachusetts 02139* Egon Pasztor’s present address: MIT Media Lab 20 Ames St. Cambridge, MA 02139 William T. Freeman, Thouis R. Jones, Egon C. Pasztor Mitsubishi Electric Research Laboratories (MERL) 201 Broadway Cambridge, MA 02139 Abstract Image-based models for computer graphics lack resolution independence: they cannot be zoomed much beyond the pixel resolution they were sampled at without a degradation of quality. Interpolating images usually results in a blurring of edges and image details. We describe image interpolation algorithms which use a database of training images to create plausible high-frequency details in zoomed images. Image pre-processing steps allow the use of image detail from regions of the training images which may look quite different from the image to be processed. These methods preserve fine details, such as edges, generate believable textures, and can give good results even after zooming multiple octaves. 1 Introduction As shown in Fig. 1, polygon-based representations of 3-dimensional objects offer resolution independence over a wide range of scales. Object boundaries remain sharp as one zooms in on the object until very close range, where faceting appears due to finite polygon