On preprocessing methods for feature-based photo-mosaic underwater

In this paper, we studied some pre-process methods that make the feature matching faster, accurate and proper to be used in the photo mosaic process. Two properties and two image processing technique were considered: channel, size, contrast enhancement, and Gaussian smoothing. We investigated how they affect the feature quantity and matching result by controling related parameters. The smallest number of features were found in the red channel. As the image size decrease, the quantity of features and the computing time were decreased in the same manner in terms of ratio. Contrast enhancement methods made image features more distinct, but its amplification in the feature quantity was not that significant. The Gaussian smoothing increased the quantity of features in the way it has the maxima with an optimal sigma, blurring parameter. When the pre-processes are used in combination, the feature matching between pair images was improved 1.6 times more in quantity.