Joint Image Bias Field Correction and Segmentation

Abstract

It is a well-known fact that in modern technology, digital images play a vital role. Image processing is used in order to accurately use these images. The main purpose of image segmentation is to separate a particular image into regions or objects that are meaningful. But image segmentation becomes very challenging when there is intensity inhomogeneity or bias field in the given image’s. Several models have been proposed in order to perform accurate segmentation but still there are issues. For this purpose we design a novel model for efficiently segmenting and bias field correction. Experimental results on medical, out-door and synthetic images validate the performance of the proposed model in contrast with the existing models.