Abstract: In order to reduce the loss of color information,we present a global nonlinear tri-mapping approach for converting color images into grayscale ones,which is based on the perceived intensity experiments.This conversion adopts the IHLS color space and builds one global nonlinear mapping with three attributes,i.e.,luminance,hue,and saturation.The global parameters are obtained by minimizing an energy function,where the first term measures the difference of color gradient and gray gradient,and the second one defines the difference of the color and gray distance between one pixel and its random sampling.This optimization method achieves the minimum by the iteration separately with three attributes.Experimental results show that our method produces pleasing results,which are close to the perceived lightness of the original color images,for a variety of color images.