Image enhancement based on skin-colour segmentation and smoothness

Abstract

The image restoration tasks represented by image denoising, super-resolution and image deblurring have a wide range of application background, and have become a research hotspot in academia and business circles. A novel image enhancement algorithm based on skin texture preservation is proposed in this paper. The mask has been obtained using the Gaussian fitting, which can have a box blur for many times and for skin feathering. The denoising smoothing image is fused with the original image mask to preserve the hair details of the original image and enhance the edge details of the contour, so as to provide more effective information for the extraction of edge features. Compared with different methods of image smoothing algorithms, this algorithm is more effective in smoothing the skin edge contour and achieving better detection of images. Experimental results show that the proposed algorithm has strong adaptive capacity and significant effect on most images detection. Specifically, it can moderately smooth the edges of the areas with many details, leaving no traces of an artificial process. The proposed algorithm with image enhancement has a wide range of practicality.