Daniele Marini

Mathematical definition and analysis of the Retinex algorithm

We present a detailed mathematical analysis of the original Retinex algorithm due to Land and McCann [J. Opt. Soc. Am. 61, 1 (1071)]. To this end, we propose an analytic formula that describes the algorithm behavior. More than one Retinex version (e.g., with and without threshold) is examined. The behavior of Retinex varying the number of paths is predicted, and its recursive iterations are mathematically analyzed using the formula. The mathematical setting presented serves as a common ground for the various Retinex implementations. Its validity is confirmed by the tests on images that we have performed.

From Retinex to Automatic Color Equalization: issues in developing a new algorithm for unsupervised color equalization

We present a comparison between two color equalization algorithms: Retinex, the famous model due to Land and McCann, and Automatic Color Equalization (ACE), a new algorithm recently presented by the authors. These two algorithms share a common approach to color equalization, but different computational models. We introduce the two models focusing on differences and common points. An analysis of their computational characteristics illustrates the way the Retinex approach has influenced ACE structure, and which aspects of the first algorithm have been modified in the second one and how. Their interesting equalization properties, like lightness and color constancy, image dynamic stretching, global and local filtering, and data driven dequantization, are qualitatively and quantitatively presented and compared, together with their ability to mimic the human visual system.

A computational approach to color adaptation effects

Abstract The human vision system has adaptation mechanisms that cannot be managed with the classic tri-stimulus color theory. The effects of these mechanisms are clearly visible in some well-known perception phenomena as color illusions, but they are always present in human observation. The discrepancy between the observation of a real scene and the observation of a picture taken from the same scene, derives from the fact that the camera does not have such mechanisms. In this paper, we propose a biologically inspired implementation of the Retinex algorithm, introduced by Land and McCann, that simulates these adaptation mechanisms, in order to reproduce some effects like dynamic adjustment, color constancy, etc. typical of the human vision system. The algorithm has been tested not only on a Mondrian-like patchwork to measure its effect, but also on different pictures, photographs and typical color illusions to test its adaptation effects. The examples demonstrate the ability of the model to emulate some characteristics of human color perception and to obtain better equalized and color-corrected images.

Color correction between gray world and white patch

Color equalization algorithms exhibit a variety of behaviors described in two differing types of models: Gray World and White Patch. These two models are considered alternatives to each other in methods of color correction. They are the basis for two human visual adaptation mechanisms: Lightness Constancy and Color Constancy. The Gray World approach is typical of the Lightness Constancy adaptation because it centers the histogram dynamic, working the same way as the exposure control on a camera. Alternatively, the White Patch approach is typical of the Color Constancy adaptation, searching for the lightest patch to use as a white reference similar to how the human visual system does. The Retinex algorithm basically belongs to the White Patch family due to its reset mechanism. Searching for a way to merge these two approaches, we have developed a new chromatic correction algorithm, called Automatic Color Equalization (ACE), which is able to perform Color Constancy even if based on Gray World approach. It maintains the main Retinex idea that the color sensation derives from the comparison of the spectral lightness values across the image. We tested different performance measures on ACE, Retinex and other equalization algorithms. The results of this comparison are presented.

YACCD: yet another color constancy database

Different image databases have been developed so far to test algorithms of color constancy. Each of them differs in the image characteristics, according to the features to test. In this paper we present a new image database, created at the University of Milano. Since a database cannot contain all the types of possible images, to limit the number of images it is necessary to make some choices and these choices should be as neutral as possible. The first image detail that we have addressed is the background. Which is the more convenient background for a color constancy test database? This choice can be affected by the goal of the color correction algorithms. In developing this DB we tried to consider a large number of possible approaches considering color constancy in a broader sense. Images under standard illuminants are presented together with particular non-standard light sources. In particular we collect two groups of lamps: with a weak and with a strong color casts. Another interesting feature is the presence of shadows, that allow to test the local effects of the color correction algorithms. The proposed DB can be used to test algorithms to recover the corresponding color under standard reference illuminants or alternatively assuming a visual appearance approach, to test algorithms for their capability to minimize color variations across the different illuminants, performing in this way a perceptual color constancy. This second approach is used to present preliminary tests. The IDB will be made available on the web.

Retinex preprocessing of uncalibrated images for color based image retrieval

In image databases, variations in imaging conditions and preprocessing may result in similar originals that exhibit a low mea- sure of similarity when color information is used in standard image retrieval methods. We examine the performance of various color- based retrieval strategies to see whether, and to what degree, the effectiveness of retrieval improves with Retinex-based preprocess- ing, regardless of the strategy adopted. The results of experiments performed on four different databases are reported and discussed.

Unsupervised corrections of unknown chromatic dominants using a Brownian-path-based Retinex algorithm

An experimental analysis of chromatic equalization based on a new implementation of the Retinex algorithm is pre- sented. The experiments are carried out on a colored Mondrian patchwork illuminated with different commercial light sources and on synthetic images generated with a photometric ray tracer using dif- ferent illuminants. Regarding the Mondrian patchwork, the spectral characteristics of the bulbs and the reflected light from each patch are measured using a commercial spectrometer. From the mea- sured data, synthetic images of the patchwork with different illumi- nants are created and processed by the Retinex algorithm. The chromatic correction capabilities of the Retinex implementation have been measured and compared with unfiltered values and with the results of another Retinex implementation and classic color equal- ization algorithms. Results show that Retinex performs an unsuper- vised color correction without requiring any information about the spectral composition of the illuminant.

Perceptual approach for unsupervised digital color restoration of cinematographic archives

The cinematographic archives represent an important part of our collective memory. We present in this paper some advances in automating the color fading restoration process, especially with regard to the automatic color correction technique. The proposed color correction method is based on the ACE model, an unsupervised color equalization algorithm based on a perceptual approach and inspired by some adaptation mechanisms of the human visual system, in particular lightness constancy and color constancy. There are some advantages in a perceptual approach: mainly its robustness and its local filtering properties, that lead to more effective results. The resulting technique, is not just an application of ACE on movie images, but an enhancement of ACE principles to meet the requirements in the digital film restoration field. The presented preliminary results are satisfying and promising.

Virtual reality as a communication process

In this work, we consider immersive Virtual Reality (VR) as a communication process between humans, mediated by computer systems, which uses interaction, visualization, and other sensory stimuli to convey information. From this viewpoint, it is relevant to understand how VR can solve a given communication problem, what is therefore the expressive power of VR system, i.e., its ability in establishing the communication, what are the guidelines to design an effective system, and what are the more relevant models of VR applications. Firstly, we try to clarify the notion of reality in Virtual Reality systems and conclude that reality is not an intrinsic characteristic of VR, rather the result of a conventional way of coding information. The purpose of coding is to lead the observer to the conclusion that the VR set is what is called in italian as verisimile (from Latin veri similis), i.e., “similar-to-the-real-thing”. So the creation of an effective VR application is an artifice or an illusion. But in order to avoid an over-reliance on the creativity of the VR designer, we intend to identify a solid ground on which different kinds of VR solutions can be considered in terms of their ability to solve the desired communication objective. To this aim, we will rely on methods derived from rhetoric to semiotics.

Tuning of perceptual technique for digital movie color restoration

In this paper we present tests and results of an automatic color fading restoration process for digitized movies. The proposed color correction method is based on the ACE model, an unsupervised color equalization algorithm based on a perceptual approach and inspired by some mechanisms of the human visual system. This perceptual approach is local, robust and does not need any user region selection or any other user supervision. However the model has a small number of parameters that has to be set once before the filtering. The tests presented in this paper aim to study these parameters and find their effect on the final result.