Current digital cameras have various automatic control systems. In automatic camera systems, extracting focusness from an image is a very important problem. Automatic extraction of the main subject makes taking photos very easy, even for an amateur photographer. Methods have been proposed to evaluate focusness by visual saliency, which assume that an area with high saliency also has high focusness. However, various differences exist between focusness and saliency. In this study, the authors compare the values between focusness and saliency maps. They evaluate the focusness of 80 images in an image evaluation experiment with 20 observers. Saliency maps are calculated using six conventional algorithms. They show that the individual variations of focusness are insignificant in images that include only one major object. Furthermore, the authors apply a GIST feature to the saliency method by using a center–surround histogram and extract focusness from images with high accuracy.