A simplified HDR image processing pipeline for digital photography

High Dynamic Range (HDR) imaging has revolutionized the digital imaging. It allows capture, storage, manipulation, and display of full dynamic range of the captured scene. As a result, it has spawned whole new possibilities for digital photography, from photorealistic to hyper-real. With all these advantages, the technique is expected to replace the conventional 8-bit Low Dynamic Range (LDR) imaging in the future. However, HDR results in an even more complex imaging pipeline including new techniques for capturing, encoding, and displaying images. The goal of this thesis is to bridge the gap between conventional imaging pipeline to the HDR’s in as simple a way as possible. We make three contributions. First we show that a simple extension of gamma encoding suffices as a representation to store HDR images. Second, gamma as a control for image contrast can be ‘optimally’ tuned on a per image basis. Lastly, we show a general tone curve, with detail preservation, suffices to tone map an image (there is only a limited need for the expensive spatially varying tone mappers). All three of our contributions are evaluated psychophysically. Together they support our general thesis that an HDR workflow, similar to that already used in photography, might be used. This said, we believe the adoption of HDR into photography is, perhaps, less difficult than it is sometimes posed to be

Color appearance in high-dynamic-range imaging

When viewing images on a monitor, we are adapted to the lighting conditions of our viewing environment as well as the monitor itself, which can be very different from the lighting conditions in which the images were taken. As a result, our perception of these photographs depends directly on the environment in which they are displayed. For high-dynamic-range images, the disconnect in the perception of scene and viewing environments is potentially much larger than in conventional film and photography. To prepare an image for display, luminance compression alone is therefore not sufficient. We propose to augment current tone reproduction operators with the application of color appearance models as an independent preprocessing step to preserve chromatic appearance across scene and display environments. The method is independent of any specific tone reproduction operator and color appearance model ( CAM) so that for each application the most suitable tone reproduction operator and CAM can be selected

Intrinsic Image Transfer for Illumination Manipulation

This paper presents a novel intrinsic image transfer (IIT) algorithm for illumination manipulation, which creates a local image translation between two illumination surfaces. This model is built on an optimization-based framework consisting of three photo-realistic losses defined on the sub-layers factorized by an intrinsic image decomposition. We illustrate that all losses can be reduced without the necessity of taking an intrinsic image decomposition under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge. Moreover, with a series of relaxations, all of them can be directly defined on images, giving a closed-form solution for image illumination manipulation. This new paradigm differs from the prevailing Retinex-based algorithms, as it provides an implicit way to deal with the per-pixel image illumination. We finally demonstrate its versatility and benefits to the illumination-related tasks such as illumination compensation, image enhancement, and high dynamic range (HDR) image compression, and show the high-quality results on natural image datasets

A novel simultaneous dynamic range compression and local contrast enhancement algorithm for digital video cameras

[[abstract]]This article addresses the problem of low dynamic range image enhancement for commercial digital cameras. A novel simultaneous dynamic range compression and local contrast enhancement algorithm (SDRCLCE) is presented to resolve this problem in a single-stage procedure. The proposed SDRCLCE algorithm is able to combine with many existent intensity transfer functions, which greatly increases the applicability of the proposed method. An adaptive intensity transfer function is also proposed to combine with SDRCLCE algorithm that provides the capability to adjustably control the level of overall lightness and contrast achieved at the enhanced output. Moreover, the proposed method is amenable to parallel processing implementation that allows us to improve the processing speed of SDRCLCE algorithm. Experimental results show that the performance of the proposed method outperforms three state-of-the-art methods in terms of dynamic range compression and local contrast enhancement.[[incitationindex]]SCI[[booktype]]電子

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

Rendering non-pictorial (Scientific) high dynamic range images

In recent years, the graphics community is seeing an increasing demand for the capture and usage of high-dynamic-range (HDR) images. Since the production of HDR imagery is not solely the domain of the visualization of real life or computer generated scenes, novel techniques are also required for imagery captured from non-visual sources such as remote sensing, medical imaging, astronomical imaging, etc. This research proposes to integrate the techniques used for the display of high-dynamic-range pictorial imagery for the practical visualization of non-pictorial (scientific) imagery for data mining and interpretation. Nine algorithms were utilized to overcome the problem associated with rendering the high-dynamic-range image data to low-dynamic-range display devices, and the results were evaluated using a psychophysical experiment. Two paired-comparison experiments and a target detection experiment were performed. Paired-comparison results indicate that the Zone System performs the best on average and the Local Color Correction method performs the worst. The results show that the performance of different encoding schemes depend on the type of data being visualized. The correlation between the preference and scientific usefulness judgments (R2 = 0.31) demonstrates that observers tend to use different criteria when judging the scientific usefulness versus image preference. The experiment was conducted using observers with expertise (Radiologists) for the Medical image to further elucidate the success of HDR rendering on these data. The results indicated that both Radiologists and Non-radiologists tend to use similar criteria regardless of their experience and expertise when judging the usefulness of rendered images. A target detection experiment was conducted to measure the detectability of an embedded noise target in the Medical image to demonstrate the effect of the tone mapping operators on target detection. The result of the target detection experiment illustrated that the detectability of targets the image is greatly influenced by the rendering algorithm due to the inherent differences in tone mapping among the algorithms

High Dynamic Range (HDR) Display Perception

Displays have undergone a huge development in the last several decades. From cathode-ray tube (CRT), liquid crystal display (LCD), to organic light-emitting diode (OLED), even Q-OLED, the new configurations of the display bring more and more functions into industry and daily life. In the recent several years, high dynamic range (HDR) displays become popular. HDR displays usually refer to that the black level of the display is darker and the peak being brighter compared with the standard dynamic range (SDR) display. Traditionally, the peak luminance level can be used as the white in characterization and calibration. However, for HDR displays, the peak luminance is higher than the traditional diffuse white level. Exploration of the perceptual diffuse white in HDR image when presented in displays is proposed, which can be beneficial to the characterizing and the optimizing the usage of the HDR display. Moreover, in addition to the ``diffuse white , 3D color gamut volume can be calculated in some specific color appearance models. Calculation and modeling of the 3D color gamut volume can be very useful for display design and better characterizing display color reproduction capability. Furthermore, the perceptional color gamut volume can be measured through psychophysical experiments. Comparison between the perceptional color gamut volume and the theoretical 3D gamut volume calculations will reveal some insights for optimizing the usage of HDR displays. Another advantage of the HDR display is its darker black compared with the SDR display. Compared with the real black object, what level of black is `perfect\u27 enough in displays? Experiments were proposed and conducted to evaluate that if the HDR display is capable of showing ``perfect black for different types of background images/patterns. A glare-based model was proposed to predict the visual ``perfect black. Additionally, the dynamic range of human vision system is very large. However, the simultaneous dynamic range of human vision system is much smaller and is important for the fine tuning usage of HDR displays. The simultaneous dynamic range was measured directly for different stimulus sizes. Also, it was found that the simultaneous dynamic range was peak luminance level dependent. A mathematical model was proposed based on the experimental data to predict the simultaneous dynamic range. Also the spatial frequency effect of the target pattern on the simultaneous dynamic range was measured and modeled. The four different assessments about HDR displays perception would provide experimental data and models for a better understanding of HDR perception and tuning of the HDR display

High-fidelity colour reproduction for high-dynamic-range imaging

The aim of this thesis is to develop a colour reproduction system for high-dynamic-range (HDR) imaging. Classical colour reproduction systems fail to reproduce HDR images because current characterisation methods and colour appearance models fail to cover the dynamic range of luminance present in HDR images. HDR tone-mapping algorithms have been developed to reproduce HDR images on low-dynamic-range media such as LCD displays. However, most of these models have only considered luminance compression from a photographic point of view and have not explicitly taken into account colour appearance. Motivated by the idea to bridge the gap between crossmedia colour reproduction and HDR imaging, this thesis investigates the fundamentals and the infrastructure of cross-media colour reproduction. It restructures cross-media colour reproduction with respect to HDR imaging, and develops a novel cross-media colour reproduction system for HDR imaging. First, our HDR characterisation method enables us to measure HDR radiance values to a high accuracy that rivals spectroradiometers. Second, our colour appearance model enables us to predict human colour perception under high luminance levels. We first built a high-luminance display in order to establish a controllable high-luminance viewing environment. We conducted a psychophysical experiment on this display device to measure perceptual colour attributes. A novel numerical model for colour appearance was derived from our experimental data, which covers the full working range of the human visual system. Our appearance model predicts colour and luminance attributes under high luminance levels. In particular, our model predicts perceived lightness and colourfulness to a significantly higher accuracy than other appearance models. Finally, a complete colour reproduction pipeline is proposed using our novel HDR characterisation and colour appearance models. Results indicate that our reproduction system outperforms other reproduction methods with statistical significance. Our colour reproduction system provides high-fidelity colour reproduction for HDR imaging, and successfully bridges the gap between cross-media colour reproduction and HDR imaging