A Paradigm for color gamut mapping of pictorial images

In this thesis, a paradigm was generated for color gamut mapping of pictorial images. This involved the development and testing of: 1.) a hue-corrected version of the CIELAB color space, 2.) an image-dependent sigmoidal-lightness-rescaling process, 3.) an image-gamut- based chromatic-compression process, and 4.) a gamut-expansion process. This gamut-mapping paradigm was tested against some gamut-mapping strategies published in the literature. Reproductions generated by gamut mapping in a hue-corrected CIELAB color space more accurately preserved the perceived hue of the original scenes compared to reproductions generated using the CIELAB color space. The results of three gamut-mapping experiments showed that the contrast-preserving nature of the sigmoidal-lightness-remapping strategy generated gamut-mapped reproductions that were better matches to the originals than reproductions generated using linear-lightness-compression functions. In addition, chromatic-scaling functions that compressed colors at a higher rate near the gamut surface and less near the achromatic axis produced better matches to the originals than algorithms that performed linear chroma compression throughout color space. A constrained gamut-expansion process, similar to the inverse of the best gamut-compression process found in this experiment, produced reproductions preferred over an expansion process utilizing unconstrained linear expansion

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

Visual quality of printed surfaces: Study of homogeneity

International audienceThis paper introduces a homogeneity assessment method for the printed versions of uniform color images. This parameter has been specifically selected as one of the relevant attributes of printing quality. The method relies on image processing algorithms from a scanned image of the printed surface, especially the computation of gray level cooccurrence matrices and of objective homogeneity attribute inspired of Haralick's parameters. The viewing distance is also taken into account when computing the homogeneity index. Resizing and filtering of the scanned image are performed in order to keep the level of details visible by a standard human observer at short and long distances. The combination of the obtained homogeneity scores on both high and low resolution images provides a homogeneity index, which can be computed for any printed version of a uniform digital image. We tested the method on several hardcopies of a same image, and compared the scores to the empirical evaluations carried out by non-expert observers who were asked to sort the samples and to place them on a metric scale. Our experiments show a good matching between the sorting by the observers and the score computed by our algorith

Image appearance modeling

Traditional color appearance modeling has recently matured to the point that available, internationally-recommended models such as CIECAM02 are capable of making a wide range of predictions to within the observer variability in color matching and color scaling of stimuli in somewhat simplified viewing conditions. It is proposed that the next significant advances in the field of color appearance modeling will not come from evolutionary revisions of these models. Instead, a more revolutionary approach will be required to make appearance predictions for more complex stimuli in a wider array of viewing conditions. Such an approach can be considered image appearance modeling since it extends the concepts of color appearance modeling to stimuli and viewing environments that are spatially and temporally at the level of complexity of real natural and man-made scenes. This paper reviews the concepts of image appearance modeling, presents iCAM as one example of such a model, and provides a number of examples of the use of iCAM in still and moving image reproduction

Print engine color management using customer image content

The production of quality color prints requires that color accuracy and reproducibility be maintained to within very tight tolerances when transferred to different media. Variations in the printing process commonly produce color shifts that result in poor color reproduction. The primary function of a color management system is maintaining color quality and consistency. Currently these systems are tuned in the factory by printing a large set of test color patches, measuring them, and making necessary adjustments. This time-consuming procedure should be repeated as needed once the printer leaves the factory. In this work, a color management system that compensates for print color shifts in real-time using feedback from an in-line full-width sensor is proposed. Instead of printing test patches, this novel attempt at color management utilizes the output pixels already rendered in production pages, for a continuous printer characterization. The printed pages are scanned in-line and the results are utilized to update the process by which colorimetric image content is translated into engine specific color separations (e.g. CIELAB-\u3eCMYK). The proposed system provides a means to perform automatic printer characterization, by simply printing a set of images that cover the gamut of the printer. Moreover, all of the color conversion features currently utilized in production systems (such as Gray Component Replacement, Gamut Mapping, and Color Smoothing) can be achieved with the proposed system

Color space adaptation for video coding

Processament d'imatges abans de ser codificades pel codificador HEVC amb la finalitat d'augmentar la qualitat i la fidelitat.[ANGLÈS] Project on the objective and subjective improvements by pre-processing images to be encoded into a video.[CASTELLÀ] Proyecto sobre la repercusión en la mejora de calidad objetiva y subjetiva del pre-procesado de imágenes a codificar con vídeo.[CATALÀ] Projecte sobre la repercussió en la millora de la qualitat objectiva i subjectiva del pre-processament d'imatges a codificar amb vídeo