The Research of Granular Computing Applied in Image Mosaic
Abstract: Based on the
existing image mosaic technology, this paper introduces the granular computing
and obtains a simplified new algorithm. The image mosaic executed by this
algorithm at first establishes correlation model on the basis of granular
computing theory, and obtains edge map of each image needing mosaic. The new
calculation method is used to calculate gradient of in different columns of
edge map, to obtain the feature point coordinates with the maximum gradient;
meanwhile, all feature points of two images are matched with each other, to
acquire the best matching point. In addition, the error-correcting mechanism is
introduced in the matching process, which is used to delete feature points with
matching error. The correlation calculation is carried out for the matching
pixels acquired by the above processing, to get the feature transformational
matrix of the two images. According to the matrix, two separated image maps map
into the same plane. The slow transitional mosaic method is applied in the
aspect of image addition plus overlap removal, so that images have no bulgy
boundary after mosaics. The whole image mosaic process shows that the given
granular computing algorithm is superior to the traditional one both in the
number of processed images and the number of processing, and the mosaic image gained
has high quality.
Author: Xiuping Zhang
Journal Code: jptkomputergg130082
