Showing papers by "Tania Pouli published in 2017"

Mixed illumination analysis in single image for interactive color grading

Abstract: Colorists often use keying or rotoscoping tools to access and edit particular colors or parts of the scene. Although necessary, this is a time-consuming and potentially imprecise process, as it is not possible to fully separate the influence of light sources in the scene from the colors of objects and actors within it. To simplify this process, we present a new solution for automatically estimating the color and influence of multiple illuminants, based on image variation analysis. Using this information, we present a new color grading tool for simply and interactively editing the colors of detected illuminants, which fits naturally in color grading workflows. We demonstrate the use of our solution in several scenes, evaluating the quality of our results by means of a psychophysical study.

Perceptual Lightness Modeling for High-Dynamic-Range Imaging

Abstract: The human visual system (HVS) non-linearly processes light from the real world, allowing us to perceive detail over a wide range of illumination. Although models that describe this non-linearity are constructed based on psycho-visual experiments, they generally apply to a limited range of illumination and therefore may not fully explain the behavior of the HVS under more extreme illumination conditions. We propose a modified experimental protocol for measuring visual responses to emissive stimuli that do not require participant training, nor requiring the exclusion of non-expert participants. Furthermore, the protocol can be applied to stimuli covering an extended luminance range. Based on the outcome of our experiment, we propose a new model describing lightness response over an extended luminance range. The model can be integrated with existing color appearance models or perceptual color spaces. To demonstrate the effectiveness of our model in high dynamic range applications, we evaluate its suitability for dynamic range expansion relative to existing solutions.

Context-aware clustering and assessment of photo collections

Abstract: To ensure that all important moments of an event are represented and that challenging scenes are correctly captured, both amateur and professional photographers often opt for taking large quantities of photographs. As such, they are faced with the tedious task of organizing large collections and selecting the best images among similar variants. Automatic methods assisting with this task are based on independent assessment approaches, evaluating each image apart from other images in the collection. However, the overall quality of photo collections can largely vary due to user skills and other factors. In this work, we explore the possibility of context-aware image quality assessment, where the photo context is defined using a clustering approach, and statistics of both the extracted context and the entire photo collection are used to guide identification of low-quality photos. We demonstrate that our method is able to flexibly adapt to the nature of processed albums and to facilitate the task of image selection in diverse scenarios.

Method and device for processing images

Abstract: A method and device for processing LDR images of a video sequence to improve image quality. The method comprises temporally decomposing successive HDR frames of a video sequence and the corresponding LDR frames and performing a comparison between the HDR and LDR frequency sub-bands. A current LDR image can then be modified on the basis of a comparison between the frequency sub-bands.

Method and device for reducing noise in a component of a picture

Abstract: The present principles relates to a method and a device for reducing noise in a component (C) of a picture, characterized in that the method comprises: - obtaining (100) a low-pass filtered component (Cf) by low-pass filtering said component (C) of the picture; - for a current pixel (i) in said component of the picture: - for at least one current neighboring pixel (j) of the current pixel (i), computing (110) a distance (D1), relative to the current neighboring pixel (j), between the value (Cf(i)) of the current pixel in the low-pass filtered component and the value (Cf(j)) of the current neighboring pixel (j) in the low-pass filtered component; - when the distances relative to said at least one neighboring pixels of the current pixel are lower than a first threshold (TH1) (120), modifying (130) the value (C(i)) of the current pixel in said component of the picture according to a linear combination of the value (C(i)) of the current pixel in said component of the picture and the value (Cf(i)) of the current pixel in the low-pass filtered component, - otherwise the value of the current pixel in said at least one component of the picture remains unchanged.

A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images

Abstract: Few tone mapping operators (TMOs) take color management into consideration, limiting compression to luminance values only. This may lead to changes in image chroma and hues which are typically managed with a post-processing step. However, current post-processing techniques for tone reproduction do not explicitly consider the target display gamut. Gamut mapping on the other hand, deals with mapping images from one color gamut to another, usually smaller, gamut but has traditionally focused on smaller scale, chromatic changes. In this context, we present a novel gamut and tone management framework for color-accurate reproduction of high dynamic range (HDR) images, which is conceptually and computationally simple, parameter-free, and compatible with existing TMOs. In the CIE LCh color space, we compress chroma to fit the gamut of the output color space. This prevents hue and luminance shifts while taking gamut boundaries into consideration. We also propose a compatible lightness compression scheme that minimizes the number of color space conversions. Our results show that our gamut management method effectively compresses the chroma of tone mapped images, respecting the target gamut and without reducing image quality.