An image enhancement technique using nonlinear transfer function and unsharp masking in multispectral endoscope

Abstract

This paper studies the realization of image processing algorithm of multispectral endoscope. The research contents include: local brightness enhancement and adaptive contrast enhancement. Firstly, this paper transforms the image from the RGB space to the HSV space, and then carries on the image enhancement processing to the V space, finally transforms to the RGB space. Local brightness enhancement algorithm divides V space image into smaller windows, and then calculates the nonlinear transfer function of each window, which enhances the pixels in the window, and finally the contrast of brightness enhanced image is restored. The adaptive contrast enhancement adopts the unsharp mask technique based on the guided filter. First of all, this paper uses guided filter to the RGB channel of the original image and gets the unsharp mask of each channel, then plus a scaled image which is the result of the original image subtracts the unsharp mask. So the enhancement of the image is achieved. This paper uses subjective evaluation criteria and enhance factor α to evaluate the effect of enhancement. And this paper compares the enhancement effect of the proposed image enhancement algorithm and the traditional algorithm. The results show that the α of histogram equalization is smallest and AINDANE method is better than histogram equalization. The proposed method has the best α. The subjective evaluation also shows that the effect of HE is not satisfactory and the proposed method enhances the detail information tremendously. The subjective and objective criteria shows that the proposed method produces better enhancement effect.