In this paper we present and compare two linear techniques for image sequence enhancement speed up that transform image contrast and color considering mainly the spatial relationship between the image areas. The first technique called LLL for Linear Local LUT is a local technique based on a Look Up Table transformation. The second technique (called PC2D) is a global technique based on a color mapping between some key zones of the original and corrected image. The need for speed up technique is especially important when processing high definition images and live videos. To test and compare the performance of the two proposed methods we have chosen the ACE (Automatic Color Equalization) technique, an unsupervised color equalization algorithm. We applied the techniques to the fields of digital cinema and digital film restoration (images with high definition) and underwater aquarium videos (live videos).
In this paper we present a tone mapping operator (TMO) for High Dynamic Range images, inspired by human visual system adaptive mechanisms. The proposed TMO is able to perform color constancy without a priori information about the scene. This is a consequence of its HVS inspiration. In our humble opinion, color constancy is very useful in TMO since we assume that it is preferable to look at an image that reproduces the color sensation rather than an image that follows classic photographic reproduction. Our proposal starts from the analysis of Retinex and ACE algorithms. Then we have extended ACE to HDR images, introducing novel features. These
are two non-linear controls: the first control allows the model to find a good trade-off between visibility and color distribution modifying the local operator at each pixel-to-pixel comparison while the second modifies the interaction between pixels estimating the local contrast. Solution towards unsupervised parameters tuning are
There is a class of non-linear filtering algorithms for digital color enhancement characterized by data driven local effect and high computational cost. In this paper we propose a new method, called LLL for Local Linear LUT, to speed-up these filters without loosing their local effect. Usually LUT based methods are global while our approach uses the principles of LUT transformation in a local way. The main idea of the proposed method is to apply the algorithm to a small sub-sampled version of the original image and to employ a modified Look Up Table technique to maintain the local filtering effect of the original algorithm. In this way three functions, one for each chromatic channel, are created for each pixel of the original image. These functions filter the original full size image in a very short time. We have tested LLL with two of these filters, a Brownian Retinex implementation (BR) and ACE (Automatic Color Equalization). The computational cost for this algorithms is very high. The proposed method increases the speed of color filtering algorithms reducing the number of pixel involved in the computation by sub-sampling the original image. Results, comparison and conclusion are presented.
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.
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.
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.