Detail preservation of morphological operations through image scaling

Abstract

Morphological techniques probe an image with a structuring element. By varying the size and the shape of structuring elements, geometrical information of different parts of an image and their interrelation can be extracted for the applications of demodulating boundary, identifying components or removing noise. While large size elements benefits eliminating noise, they may be disadvantageous for preserving details in an image. Taking this into consideration, in this paper, we propose an image scaling method that will preserve detailed information when applying morphological operations to remove noise. First, a binary image is obtained, from which a Preservation Ratio Scalar (PRS) is calculated. The PRS is used for upscaling the image before morphological operations, which aims at preserving structural fine details otherwise eliminated in the original image. Finally, the morphological operator processed image is downscaled using the PRS. Experiments of target detection demonstrated the effectiveness of the proposed method in preserving the structural details such as edges while eliminating noises.