Painting-like Image Emphasis based on Human Vision Systems

Regional image emphasis is often evident in paintings and illustrations. This technique increases local contrast while reducing global contrast by amplifying image intensity on shadowed surfaces, reducing intensity on illuminated surfaces, and then expanding contrast at intensity edges. The effects are assumed to result from the visual processing needed to interpolate the real world onto canvas. Therefore, we propose an intensity emphasis method based on human vision. This method simulates the adaptation of photoreceptor cells and the lateral inhibition of receptive fields. These attributes of a vision systemare realized by computation of relative intensity and differential intensity in small areas. The proposed method can successfully generate painting-like artifacts, which greatly improves the perception of visual elements displayed in an image. Since the method efficiently reduces the dynamic range of images, it can be used for displaying highlighted images on standard graphic monitors. Experiments on a computer-generated image and a photograph confirm the advantages of our method