Appearance-based image splitting for HDR display systems

High dynamic range displays that incorporate two optically-coupled image planes have recently been developed. This dual image plane design requires that a given HDR input image be split into two complementary standard dynamic range components that drive the coupled systems, therefore there existing image splitting issue. In this research, two types of HDR display systems (hardcopy and softcopy HDR display) are constructed to facilitate the study of HDR image splitting algorithm for building HDR displays. A new HDR image splitting algorithm which incorporates iCAM06 image appearance model is proposed, seeking to create displayed HDR images that can provide better image quality. The new algorithm has potential to improve image details perception, colorfulness and better gamut utilization. Finally, the performance of the new iCAM06-based HDR image splitting algorithm is evaluated and compared with widely spread luminance square root algorithm through psychophysical studies

Expanding Dimensionality in Cinema Color: Impacting Observer Metamerism through Multiprimary Display

Television and cinema display are both trending towards greater ranges and saturation of reproduced colors made possible by near-monochromatic RGB illumination technologies. Through current broadcast and digital cinema standards work, system designs employing laser light sources, narrow-band LED, quantum dots and others are being actively endorsed in promotion of Wide Color Gamut (WCG). Despite artistic benefits brought to creative content producers, spectrally selective excitations of naturally different human color response functions exacerbate variability of observer experience. An exaggerated variation in color-sensing is explicitly counter to the exhaustive controls and calibrations employed in modern motion picture pipelines. Further, singular standard observer summaries of human color vision such as found in the CIE’s 1931 and 1964 color matching functions and used extensively in motion picture color management are deficient in recognizing expected human vision variability. Many researchers have confirmed the magnitude of observer metamerism in color matching in both uniform colors and imagery but few have shown explicit color management with an aim of minimized difference in observer perception variability. This research shows that not only can observer metamerism influences be quantitatively predicted and confirmed psychophysically but that intentionally engineered multiprimary displays employing more than three primaries can offer increased color gamut with drastically improved consistency of experience. To this end, a seven-channel prototype display has been constructed based on observer metamerism models and color difference indices derived from the latest color vision demographic research. This display has been further proven in forced-choice paired comparison tests to deliver superior color matching to reference stimuli versus both contemporary standard RGB cinema projection and recently ratified standard laser projection across a large population of color-normal observers

Individual Colorimetric Observers for Personalized Color Imaging

Colors are typically described by three values such as RGB, XYZ, and HSV. This is rooted to the fact that humans possess three types of photoreceptors under photopic conditions, and human color vision can be characterized by a set of three color matching functions (CMFs). CMFs integrate spectra to produce three colorimetric values that are related to visual responses. In reality, large variations in CMFs exist among color-normal populations. Thus, a pair of two spectrally different stimuli might be a match for one person but a mismatch for another person, also known as observer metamerism. Observer metamerism is a serious issue in color-critical applications such as soft proofing in graphic arts and color grading in digital cinema, where colors are compared on different displays. Due to observer metamerism, calibrated displays might not appear correctly, and one person might disagree with color adjustments made by another person. The recent advent of wide color gamut display technologies (e.g., LEDs, OLEDs, lasers, and Quantum Dots) has made observer metamerism even more serious due to their spectrally narrow primaries. The variations among normal color vision and observer metamerism have been overlooked for many years. The current typical color imaging workflow uses a single standard observer assuming all the color-normal people possess the same CMFs. This dissertation provides a possible solution for observer metamerism in color-critical applications by personalized color imaging introducing individual colorimetric observers. In this dissertation, at first, color matching data were collected to derive and validate CMFs for individual colorimetric observers. The data from 151 color-normal observers were obtained at four different locations. Second, two types of individual colorimetric observer functions were derived and validated. One is an individual colorimetric observer model, an extension of the CIE 2006 physiological observer incorporating eight physiological parameters to model individuals in addition to age and field size inputs. The other is a set of categorical observer functions providing a more convenient approach towards the personalized color imaging. Third, two workflows were proposed to characterize human color vision: one using a nomaloscope and the other using proposed spectral pseudoisochromatic images. Finally, the personalized color imaging was evaluated in a color image matching study on an LCD monitor and a laser projector and in a perceived color difference study on a SHARP Quattron display. The personalized color imaging was implemented using a newly introduced ICC profile, iccMAX

The effect of image size on the color appearance of image reproductions

Original and reproduced art are usually viewed under quite different viewing conditions. One of the interesting differences in viewing condition is size difference. The main focus of this research was investigation of the effect of image size on color perception of rendered images. This research had several goals. The first goal was to develop an experimental paradigm for measuring the effect of image size on color appearance. The second goal was to identify the most affected image attributes for changes of image size. The final goal was to design and evaluate algorithms to compensate for the change of visual angle (size). To achieve the first goal, an exploratory experiment was performed using a colorimetrically characterized digital projector and LCD. The projector and LCD were light emitting devices and in this sense were similar soft-copy media. The physical sizes of the reproduced images on the LCD and projector screen could be very different. Additionally, one could benefit from flexibility of soft-copy reproduction devices such as real-time image rendering, which is essential for adjustment experiments. The capability of the experimental paradigm in revealing the change of appearance for a change of visual angle (size) was demonstrated by conducting a paired-comparison experiment. Through contrast matching experiments, achromatic and chromatic contrast and mean luminance of an image were identified as the most affected attributes for changes of image size. Measurement of the extent and trend of changes for each attribute were measured using matching experiments. Proper algorithms to compensate for the image size effect were design and evaluated. The correction algorithms were tested versus traditional colorimetric image rendering using a paired-comparison technique. The paired-comparison results confirmed superiority of the algorithms over the traditional colorimetric image rendering for the size effect compensation

Colorimetric tolerances of various digital image displays

Visual experiments on four displays (two LCD, one CRT and hardcopy) were conducted to determine colorimetric tolerances of images systematically altered via three different transfer curves. The curves used were: Sigmoidal compression in L*, linear reduction in C*, and additive rotations in hab. More than 30 observers judged the detectability of these alterations on three pictorial images for each display. Standard probit analysis was then used to determine the detection thresholds for the alterations. It was found that the detection thresholds on LCD\u27s were similar or lower than for the CRT\u27s in this type of experiment. Summarizing pixel-by-pixel image differences using the 90th percentile color difference in E*ab was shown to be more consistent than similar measures in E94 and a prototype E2000. It was also shown that using the 90th percentile difference was more consistent than the average pixel wise difference. Furthermore, SCIELAB pre-filtering was shown to have little to no effect on the results of this experiment since only global color-changes were applied and no spatial alterations were used

Optimal Linear RGB-to-XYZ Mapping for Color Display Calibration

Color display calibration, in part, involves mapping input RGB values to corresponding output values in a standardized color space such as CIE XYZ. A linear model for RGB-to- XYZ mapping is based on a 3-by-3 linear transformation matrix T mapping data from (linearized) RGB to XYZ. Such a mapping is often determined by least squares regression on the difference between predicted and measured XYZ values. However, since displays are calibrated for viewing by human observers, it likely would be better to optimize relative to a perceptually uniform color space. Two new methods are proposed which optimize the total error relative to CIELAB or CIEDE2000. The first method uses weighted least squares with weights based on the rate of change of CIELAB coordinates as a function of change in XYZ. The second method uses Nedler-Mead nonlinear optimization to minimize directly in CIELAB or CIEDE200. Experiments based on calibrating 2 CRT monitors, 3 LCD monitors and 2 LCD projectors show significantly better results than the standard least squares calibration

The Effects of Multi-channel Visible Spectrum Imaging on Perceived Spatial Image Quality and Color Reproduction Accuracy

Two paired-comparison psychophysical experiments were performed. The stimuli consisted of six image types resultingfrom several multispectral image-capture and reconstruction techniques. A seventh image type, color-managed images from a high-end consumer camera, was also included in thefirst experiment to compare the accuracy of commercial RGB imaging. The images were evaluated under simulated daylight (6800K) and incandescent (2700K) illumination. The first experiment evaluated color reproduction accuracy. Under simulated daylight, the subjects judged all of the images to have the same color accuracy, except the consumer camera image which was significantly worse. Under incandescent illumination, all the images, including the consumer camera, had equivalent performance. The second experiment evaluated image quality. The results of this experiment were highly target dependent. A subsequent image registration experiment showed that the results of the image quality experiment were affected by image registration to some degree. An analysis of the color reproduction accuracy and image quality experiments combined showed that the consumer camera image type was preferred the least over all. The most preferred image types were the thirty-one-channel image type and both six-channel image types created using RGB filters along with a Wratten filter, with eigenvector analysis and pseudo-inverse transformations

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