Super-resolution Image Created from a Sequence of Images with Application of Character Recognition

Super-resolution techniques allow combine multiple images of the same scene to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The objective of this work is to develop efficient algorithm, robust and automated fusion image frames to obtain a super-resolution image. Image registration is a fundamental step in combining several images that make up the scene. Our research is based on the determination and extraction of characteristics defined by the SIFT and RANSAC algorithms for automatic image registration. We use images containing characters and perform recognition of these characters to validate and show the effectiveness of our proposed method. The distinction of this work is the way to get the matching and merging of images because it occurs dynamically between elements common images that are stored in a dynamic matrix.

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