Improving SLI Performance in Optically Challenging Environments

The construction of 3D models of real-world scenes using non-contact methods is an important problem in computer vision. Some of the more successful methods belong to a class of techniques called structured light illumination (SLI). While SLI methods are generally very successful, there are cases where their performance is poor. Examples include scenes with a high dynamic range in albedo or scenes with strong interreflections. These scenes are referred to as optically challenging environments. The work in this dissertation is aimed at improving SLI performance in optically challenging environments. A new method of high dynamic range imaging (HDRI) based on pixel-by-pixel Kalman filtering is developed. Using objective metrics, it is show to achieve as much as a 9.4 dB improvement in signal-to-noise ratio and as much as a 29% improvement in radiometric accuracy over a classic method. Quality checks are developed to detect and quantify multipath interference and other quality defects using phase measuring profilometry (PMP). Techniques are established to improve SLI performance in the presence of strong interreflections. Approaches in compressed sensing are applied to SLI, and interreflections in a scene are modeled using SLI. Several different applications of this research are also discussed

Convolutional sparse coding for high dynamic range imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially-varying pixel exposures. In this paper, we propose a novel algorithm to recover high-quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently-introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher-quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform

Contemplation of tone mapping operators in high dynamic range imaging

The technique of tone mapping has found widespread popularity in the modern era owing to its applications in the digital world. There are a considerable number of tone mapping techniques that have been developed so far. One method may be better than the other in some cases which is determined by the requirement of the user. In this paper, some of the techniques for tone mapping/tone reproduction of high dynamic range images have been contemplated. The classification of tone mapping operators has also been given. However, it has been found that these techniques lack in providing quality of service visualization of high dynamic range images. This paper has tried to highlight the drawbacks in the existing traditional methods so that the tone-mapped techniques can be enhanced

A robust patch-based synthesis framework for combining inconsistent images

Current methods for combining different images produce visible artifacts when the sources have very different textures and structures, come from far view points, or capture dynamic scenes with motions. In this thesis, we propose a patch-based synthesis algorithm to plausibly combine different images that have color, texture, structural, and geometric inconsistencies. For some applications such as cloning and stitching where a gradual blend is required, we present a new method for synthesizing a transition region between two source images, such that inconsistent properties change gradually from one source to the other. We call this process image melding. For gradual blending, we generalized patch-based optimization foundation with three key generalizations: First, we enrich the patch search space with additional geometric and photometric transformations. Second, we integrate image gradients into the patch representation and replace the usual color averaging with a screened Poisson equation solver. Third, we propose a new energy based on mixed L2/L0 norms for colors and gradients that produces a gradual transition between sources without sacrificing texture sharpness. Together, all three generalizations enable patch-based solutions to a broad class of image melding problems involving inconsistent sources: object cloning, stitching challenging panoramas, hole filling from multiple photos, and image harmonization. We also demonstrate another application which requires us to address inconsistencies across the images: high dynamic range (HDR) reconstruction using sequential exposures. In this application, the results will suffer from objectionable artifacts for dynamic scenes if the inconsistencies caused by significant scene motions are not handled properly. In this thesis, we propose a new approach to HDR reconstruction that uses information in all exposures while being more robust to motion than previous techniques. Our algorithm is based on a novel patch-based energy-minimization formulation that integrates alignment and reconstruction in a joint optimization through an equation we call the HDR image synthesis equation. This allows us to produce an HDR result that is aligned to one of the exposures yet contains information from all of them. These two applications (image melding and high dynamic range reconstruction) show that patch based methods like the one proposed in this dissertation can address inconsistent images and could open the door to many new image editing applications in the future

Transillumination and HDR Imaging for Proximal Caries Detection

The purpose of this study was to develop an in vitro model for the validation of near-infrared transillumination (NIRT) for proximal caries detection, to enhance NIRT with high-dynamic-range imaging (HDRI), and to compare both methods, using micro-computed tomography (mu CT) as a reference standard. Both proximal surfaces of 53 healthy or decayed permanent human teeth were examined using the Diagnocam (DC) (KaVo) and NIRT with HDRI (NIRT-HDRI). NIRT was combined with HDRI to improve the diagnostic performance by reducing under- and overexposed image areas. For NIRT-HDRI, an exposure series was captured and merged into a single HDR image. A classification was applied according to lesion depth. All surfaces were assessed twice by 2 trained examiners, and additionally with mu CT for validation. The Kappa statistic was used to calculate inter-rater reliability and agreement between DC and NIRT-HDRI. Inter-rater reliability (weighted Kappa, w) showed very good agreement for the DC (0.90) and NIRT-HDRI (0.96). The overall agreement (w) was almost perfect (0.85). In the individual categories (0 to 4), the agreement (simple Kappa) ranged from almost perfect (category 4) to moderate (1 and 2) to substantial (categories 0 and 3). Sensitivity and specificity of sound surfaces, enamel, and dentin caries ranged from 0.57 to 0.99 and were similar for both methods in the different categories. NIRT-HDRI had a higher sensitivity for sound surfaces and enamel caries, as well as a higher specificity for dentin caries. Regarding the obtained images, HDRI allowed for the detection of caries within a greater range of luminance levels, resulting in a more detailed visualization of structures without under- or overexposure. However, HDRI this did not improve the diagnostics significantly. Distinguishing between a processed demineralized enamel and dentin lesions appears to be a problem specific to NIRT and cannot be balanced using HDRI

A Game Engine as a Generic Platform for Real-Time Previz-on-Set in Cinema Visual Effects

International audienceWe present a complete framework designed for film production requiring live (pre) visualization. This framework is based on a famous game engine, Unity. Actually, game engines possess many advantages that can be directly exploited in real-time pre-vizualization, where real and virtual worlds have to be mixed. In the work presented here, all the steps are performed in Unity: from acquisition to rendering. To perform real-time compositing that takes into account occlusions that occur between real and virtual elements as well as to manage physical interactions of real characters towards virtual elements, we use a low resolution depth map sensor coupled to a high resolution film camera. The goal of our system is to give the film director's creativity a flexible and powerful tool on stage, long before post-production

Practical photoquantity measurement using a camera

International audienceAn image output by a camera is generally not a faithful representation of the real scene, because it undergoes a series of radiometric disturbances during the imaging process. This paper proposes a method for obtaining a more accurate measure of the light seen by a camera. Our method requires no specific calibration apparatus and only minimal supervision. Nevertheless, it is quite comprehensive, since it accounts for response function, exposure, vignetting, spatial non-uniformity of the sensor and colour balancing. Our method works in two steps. First, the camera is calibrated off-line, in a photoquantity sense. Then, the photoquantity of any scene can be estimated in-line. Our method is therefore geared to a wide range of computer vision applications where a camera is expected to give a measurement of the visible light. The paper starts by presenting a photoquantity model of the camera imaging process. It then describes the key steps of calibration and correction method. Finally, results are given and analyzed to evaluate the relevance of our approach

Objective and subjective assessment of perceptual factors in HDR content processing

The development of the display and camera technology makes high dynamic range (HDR) image become more and more popular. High dynamic range image give us pleasant image which has more details that makes high dynamic range image has good quality. This paper shows us the some important techniques in HDR images. And it also presents the work the author did. The paper is formed of three parts. The first part is an introduction of HDR image. From this part we can know why HDR image has good quality