In our daily lives dealing with images, we have the mental notion that we are reproducing an original. This notion is generally helpful in guiding image and color processing decisions, but often it turns into a hindrance when artificial constraints are imposed on the conceptual original. This paper describes some scenarios in which a broader view than “reproduction” might be beneficial.

Impairments in imaging systems are discussed in the areas of lens vignetting, camera spectral sensitivities, reproduction gamut, tone reproduction, luminance-chrominance coding, and spatial resolution. The causes of these impairments are reviewed, and their importance discussed. Means of providing corrections are considered, and the factors determining whether such means are used or not, are reviewed; the type of scene being imaged is shown to be decisive in many cases.

Recently it has been claimed that some early Renaissance painters used concave mirrors to project real inverted images onto their supports (paper, canvas, oak panel, …) which they then traced or painted over, and that this was a key source of an apparent increase in naturalism and realism in European painting around 1420. This bold theory makes implicit and explicit assumptions about the illumination and associated optical technology used for such projections. We compute and experimentally verify that the illumination requirements of the projection method are quite severe, and that in most cases subjects would have had to have been illuminated by direct sunlight, which seems unlikely for many specific paintings. We show how modern “re-enactments” of the theory's procedure in this regard are sometimes misleading or flawed, generally biased in favor of the theory. In certain versions, and for certain paintings, the theory also has testable implications for the color in final paintings. Through computer manipulation of digital images of key Renaissance paintings, we test informally whether it is faithful reproduction of form and contour or instead of color that best explains the naturalism in early Renaissance paintings, and conclude that it is subtleties in color. We demonstrate how the optical projection technique never aids in the accurate rendering of color, and in certain implementations severely impedes in the accurate rendering of color. Our analysis of color and illumination argues against the projection theory generally, and further supports conclusions from image analyses of specific paintings in the debate.

An interactive program has been developed to assist in the design of new goniochromatic colors. The program gives the user a unique set of controls over a second order polynomial that defines these color families at a sequence of aspecular reflection angles. One approach, based on traditional metallic colors, allows the user to adjust the average hue, saturation, and brightness of all of the colors interpolated by the polynomial. Another method, appropriate for the newer effect colors, permits the designer to establish face and flop colors to be reached at either end of the interpolation. In a final technique, variations produced by adjusting model parameters can be evaluated and selected.

For over 3 decades, computer graphics technology has been developed to simulate physically accurate image of real scene. Meanwhile, useful tone mapping methods have been developed to map luminance range of the simulated image into that of usual monitor without perceptual distortion. However, it is difficult to reproduce accurate glossiness of real objects within the limited monitor luminance range. This also causes inaccurate glossiness sequence among several reproduced images. In this paper, relative-glossiness matching technique is proposed for reliable business to business (B to B) e-commerce system on 3D prints such as beverage cans, PET bottles, snack packages, and so on. The relative-glossiness-matching technique is introduced to preserve perceptual ratio of glossiness of the real 3D print objects in reproduced images. We also propose two operations to control surface-texture gloss and contrast gloss of reproduced images in Hunter's classification for physical gloss; adding Gaussian noise to surface normal in rendering process and scaling specular reflection in tone mapping. Procedure of subjective evaluation to determine the standard deviation of Gaussian noise and scaling factor for specular reflection is described. An experiment for the relative-glossiness matched images is performed using four types of real papers shaped into 3D cylinders. It was visually confirmed that the reproduced images preserved the glossiness sequence of the real 3D cylinder.

This paper proposes a method for estimating a set of spectral-power distributions of an omnidirectional light distribution from images taken by a camera aimed at a mirrored ball. First, we introduce some measuring systems that are designed for acquiring ambient light at any location in natural scenes. Second, a mapping algorithm is determined between coordinates on the ball and light rays in the world. Then we create images representing the omnidirectional light distribution. Third, the illuminant spectral-power distribution is recovered using the RGB image data and the calibrated reflectance data of the ball. Fourth, a CG image is created using the estimated omnidirectional illuminant distribution and a spectral-reflectance model for various objects. An experiment is conducted in our university gym.

Color imaging systems are continuously improving, and have now improved to the point of capturing high dynamic range scenes. Unfortunately most commercially available color display devices, such as CRTs and LCDs, are limited in their dynamic range. It is necessary to tone-map, or render, the high dynamic range images in order to display them onto a lower dynamic range device. This paper describes the use of an image appearance model, iCAM, to render high dynamic range images for display. Image appearance models have greater flexibility over dedicated tone-scaling algorithms as they are designed to predict how images perceptually appear, and not designed for the singular purpose of rendering. In this paper we discuss the use of an image appearance framework, and describe specific implementation details for using that framework to render high dynamic range images.

The visual system has the ability to see and obtain detailed information from a highly dynamic range of a scene. For example, a person can observe items in one range by observing the inside of a dim room as well as outside through a window. An algorithm for high dynamic range compression that can be applied for still and video images is presented. This algorithm is based on a biological model that is also suggested for wide dynamic range and lightness constancy. It succeeded in automatically compressing the dynamic range of images to a ‘human vision appearance’ (as is commonly required in cameras and displays) while maintaining and even improving contrast. The biological basis is expressed as retinal mechanisms of adaptation (gain control), both ‘local’, and ‘remote’, that enable also video image applications by taking into account the dynamics of human adaptation mechanisms. The results indicate the significant and robust contribution of adaptation mechanisms in image appearance, and have been found appropriate for next generation High dynamic range cameras (CMOS based).

Contrast is the well-known observation in which a gray in a white surround appears darker than in a black one. An example is a 32 by 32 pixel gray area subtending 0.75 degrees visual angle on a black background - 256 pixels on a side. The gray appears darker when surrounded by a band of white - 12 pixels wide. The white band is made up of 2112 individual white pixels. If these white pixels are redistributed uniformly in the black background the gray appears much lighter. This paper measures the gray appearance as influenced by 2112 white pixels in 27 different spatial configurations. The set of different spatial patterns of white pixels that generate the same matching lightness for gray are defined as equivalent backgrounds. The paper then analyzes the spatial properties of equivalent backgrounds. Gray appears darkest when the solid white surrounds the gray and is contiguous with it. In the case of the distributed white pixels, the gray appears lighter. This paper presents an analysis of the spatial properties of intermediate surrounds that give the gray center equal visual appearances.

This work presents a framework for image classification based on region information. The main application of this framework is for automatic color correction of real-scene images. Class specific color correction is already implemented in some systems, but image classification usually relies on global image features only. Our region-based approach shows a significant improvement over previously achieved classification for a variety of critical image classes. Improved image classification can directly be translated into improved automatic color correction.