Abstract:

Aiming at the characteristics such as low contrast,unclear imaging,over-dark or over-bright overall imaging and noise interference in ultraviolet image itself,a Curvelet domain ultraviolet image enhancement algorithm was proposed based on the masking characteristics of human vision.Firstly,the ultraviolet image information was decomposed to different scales and direction sub-bands by Curvelet transform.Secondly,the HVS model was established according to each sub-band,and with its masking characteristics,the nonlinear gain of the high frequency component was used to improve the image contrast.Meanwhile,the low frequency component of nonlinear grayscale stretching could improve the overall brightness of the image.Finally,the processed high and low frequency components were reconstructed by Curvelet backward to obtain enhanced ultraviolet images.The experimental results show that the enhanced image accords with the extraction of image information from human vision and highlights the contour information of edge and target.In addition,it has obvious effect in subjective vision and quantitative index.

Key words: ultraviolet image, masking characteristic, Curvelet transform, nonlinear gain, enhancement