View Full Document

IMAGE INTERPOLATION USING CLASSIFICATION AND STITCHING



View the full content.
View Full Document
View Full Document

3 views

Unformatted text preview:

IMAGE INTERPOLATION USING CLASSIFICATION AND STITCHING Nickolaus Mueller Truong Q Nguyen University of California San Diego Department of Electrical and Computer Engineering 9500 Gilman Drive MC 0407 La Jolla CA 92093 0407 ABSTRACT Image interpolation is a well studied signal processing application that continues to receive substantial attention from the research community It has been recognized that taking into account the presence of edges in an image can significantly improve the resulting interpolated image Many techniques modify the interpolation method in the presence of edges to avoid common artifacts such as blurring blocking and ringing We propose to improve upon this idea by fusing the best features of several interpolation methods This can be done using a novel region classification algorithm to determine which method is best suited to a particular region From this information we can use image mosaic techniques to fuse the methods into a result that contains both sharp edges and detailed textures Index Terms image interpolation mosaicing multiresolution transforms block matching image denoising 1 INTRODUCTION The goal of image interpolation is to produce a higher resolution version of a given image Several potential applications exist for image interpolation such as enhancing the resolution of an image taken by a low quality camera on a cell phone or displaying video from a low resolution source on a high definition television Basic techniques such as bilinear and bicubic interpolation accomplish this at a low cost but they sacrifice quality of the final image by assuming that the underlying true image is piecewise polynomial In recent literature several algorithms improve the subjective quality of an interpolated image by taking into account edge regions of an image during interpolation The methods employed by these algorithms range from explicitly avoiding interpolation across edges 1 2 to probabilistic formulations that involve calculating an optimal



Access the best Study Guides, Lecture Notes and Practice Exams

Loading Unlocking...
Login

Join to view IMAGE INTERPOLATION USING CLASSIFICATION AND STITCHING and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view IMAGE INTERPOLATION USING CLASSIFICATION AND STITCHING and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?