The histeq function is typically used to enhance the contrast of grayscale images. However, it is also possible to use histeq on color images by applying it separately to each color channel (red, green, and blue) of the image. Here are the general steps to use histeq function on color images:

1. Convert the color image from RGB (Red Green Blue) to a different color space, such as HSV (Hue Saturation Value) or YCbCr (Luma Chroma) using the rgb2hsv or rgb2ycbcr function respectively. This is because histeq function works better on luminance or brightness channels rather than on color channels.

2. Apply the histeq function on the luminance or brightness channel of the converted image. In the case of the HSV color space, the brightness channel is the V channel, while in the YCbCr color space, the luminance channel is the Y channel.

3. Convert the image back to the RGB color space using the hsv2rgb or ycbcr2rgb function, depending on the color space used in step 1.

Here's an example code snippet to perform histogram equalization on a color image using the histeq function in MATLAB: 

% Read color image
img = imread('color_image.jpg');

% Convert the image to the YCbCr color space
img_ycbcr = rgb2ycbcr(img);

% Apply histogram equalization on the luminance channel
img_ycbcr(:,:,1) = histeq(img_ycbcr(:,:,1));

% Convert the image back to the RGB color space
img_histeq = ycbcr2rgb(img_ycbcr);

% Display the original and histogram equalized images side by side
imshowpair(img, img_histeq, 'montage');

Note that the imshowpair function is used here to display the original and histogram equalized images side by side for comparison.