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This paper presents strategies of the target localization in passive bistatic radar in the presence of multiple receivers and non cooperative illuminators. One of the algorithms based on ellipsoid intersections is analyzed. The individual target position is calculated from the bistatic range (BR) measurements using closed form equation based on the time difference of arrival (TDOA) algorithm. Aim of the algorithm is to find the intersection of ellipsoids in 3D space, which is a challenging task. The main performance issues, complexity of calculation and limitation are presented. A method of complexity and a memory requirement reduction using the direction of arrival is proposed and analyzed. The paper also deals with parallel implementation of Spherical Intersections algorithm using Graphics Processing Unit (GPU).

We address the problem of communicating contrasts in images degraded with respect to their original due to processing with computer graphics algorithms. Such degradation can happen during the tone mapping of high dynamic range images, or while rendering scenes with low contrast shaders or with poor lighting. Inspired by a family of known perceptual illusions: Craik-O’Brien-Cornsweet, we enhance contrasts by modulating brightness at the edges to create countershading proles. We generalize unsharp masking by coupling it with a multi-resolution local contrast metric to automatically create the countershading proles from the sub-band components which are individually adjusted to each corrected feature to best enhance contrast with respect to the reference. Additionally, we employ a visual detection model to assure that our enhancements are not perceived as objectionable halo artifacts. The overall appearance of images remains mostly unchanged and the enhancement is achieved within the available dynamic range. We use our method to post-correct tone mapped images and improve images using their depth information.

High Dynamic Range (HDR) images capture the full range of luminance present in real world scenes, and unlike Low Dynamic Range (LDR) images, can simultaneously contain detailed information in the deepest of shadows and the brightest of light sources. For display or aesthetic purposes, it is often necessary to perform tone mapping, which creates LDR depictions of HDR images at the cost of contrast information loss. The purpose of this work is two-fold: to analyze a displayed LDR image against its original HDR counterpart in terms of perceived contrast distortion, and to enhance the LDR depiction with perceptually driven colour adjustments to restore the original HDR contrast information. For analysis, we present a novel algorithm for the characterization of tone mapping distortion in terms of observed loss of global contrast, and loss of contour and texture details. We classify existing tone mapping operators accordingly. We measure both distortions with perceptual metrics that enable the automatic and meaningful enhancement of LDR depictions. For image enhancement, we identify artistic and photographic colour techniques from which we derive adjustments that create contrast with colour. The enhanced LDR image is an improved depiction of the original HDR image with restored contrast information.

Due to rapid technological progress in high dynamic range (HDR) video capture and display, the efficient storage and transmission of such data is crucial for the completeness of any HDR imaging pipeline. We propose a new approach for inter-frame encoding of HDR video, which is embedded in the well-established MPEG-4 video compression standard. The key component of our technique is luminance quantization that is optimized for the contrast threshold perception in the human visual system. The quantization scheme requires only 10--11 bits to encode 12 orders of magnitude of visible luminance range and does not lead to perceivable contouring artifacts. Besides video encoding, the proposed quantization provides perceptually-optimized luminance sampling for fast implementation of any global tone mapping operator using a lookup table. To improve the quality of synthetic video sequences, we introduce a coding scheme for discrete cosine transform (DCT) blocks with high contrast. We demonstrate the capabilities of HDR video in a player, which enables decoding, tone mapping, and applying post-processing effects in real-time. The tone mapping algorithm as well as its parameters can be changed interactively while the video is playing. We can simulate post-processing effects such as glare, night vision, and motion blur, which appear very realistic due to the usage of HDR data.

Contrast in image processing is typically scaled using a power function (gamma) where its exponent specifies the amount of the physical contrast change. While the exponent is normally constant for the whole image, we observe that such scaling leads to perceptual nonuniformity in the context of high dynamic range (HDR) images. This effect is mostly due to lower contrast sensitivity of the human eyes for the low luminance levels. Such levels can be reproduced by an HDR display while they can not be reproduced by standard display technology. We conduct two perceptual experiments on a complex image: contrast scaling and contrast discrimination threshold , and we derive a model which relates changes of physical and perceived contrasts at different luminance levels. We use the model to adjust the exponent value such that we obtain better perceptual uniformity of global and local contrast scaling in complex images.© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Both high dynamic range images and their tone mapped correspondents contain relative luminance values which have to be mapped on a scale of available gray levels of a display. Such mapping includes brightness adjustment, which has a direct impact on the final image appearance and the observers' assessment of image quality. We conduct a psychophysical experiment in which subjects adjust image brightness to match their preference. We observe that the brightness choice is consistent across subjects and is primarily affected by image content. We investigate popular methods for automatic brightness adjustment and show a significant inaccuracy for a group of images. The incorrect brightness adjustment degrades in these cases perceived image quality. We identify characteristics of images that are highly correlated with the subjects' choice of brightness and develop an improved model for the brightness adjustment.

Vast majority of digital images and video material stored today can capture only a fraction of visual information visible to the human eye and does not offer sufficient quality to fully exploit capabilities of new display devices. High dynamic range (HDR) image and video formats encode the full visible range of luminance and color gamut, thus offering ultimate fidelity, limited only by the capabilities of the human eye and not by any existing technology. In this paper we demonstrate how existing image and video compression standards can be extended to encode HDR content efficiently. This is achieved by a custom color space for encoding HDR pixel values that is derived from the visual performance data. We also demonstrate how HDR image and video compression can be designed so that it is backward compatible with existing formats.

The advances in high dynamic range (HDR) imaging, especially in the display and camera technology, have a significant impact on the existing imaging systems. The assumptions of the traditional low-dynamic range imaging, designed for paper print as a major output medium, are ill suited for the range of visual material that is shown on modern displays. For example, the common assumption that the brightest color in an image is white can be hardly justified for high contrast LCD displays, not to mention next generation HDR displays, that can easily create bright highlights and the impression of self-luminous colors. We argue that high dynamic range representation can encode images regardless of the technology used to create and display them, with the accuracy that is only constrained by the limitations of the human eye and not a particular output medium. To facilitate the research on high dynamic range imaging, we have created a software package (http://pfstools.sourceforge.net/) capable of handling HDR data on all stages of image and video processing. The software package is available as open source under the General Public License and includes solutions for high quality image acquisition from multiple exposures, a range of tone mapping algorithms and a visual difference predictor for HDR images. Examples of shell scripts demonstrate how the software can be used for processing single images as well as video sequences.

An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Tremendous progress in the development and accessibility of high dynamic range (HDR) technology that has happened just recently results in fast proliferation of HDR synthetic image sequences and captured HDR video. When properly processed, such HDR data can lead to very convincing and realistic results even when presented on traditional low dynamic range (LDR) display devices. This requires real-time local contrast compression (tone mapping) with simultaneous modeling of important in HDR image perception effects such as visual acuity, glare, day and night vision. We propose a unified model to include all those effects into a common computational framework, which enables an efficient implementation on currently available graphics hardware. We develop a post processing module which can be added as the final stage of any real-time rendering system, game engine, or digital video player, which enhances the realism and believability of displayed image streams.

Global illumination dramatically improves realistic appearance of rendered scenes, but usually it is neglected in VR systems due to its high costs. In this work we present an efficient global illumination solution specifically tailored for those CAVE applications, which require an immediate response for dynamic light changes and allow for free motion of the observer, but involve scenes with static geometry. As an application example we choose the car interior modeling under free driving conditions. We illuminate the car using dynamically changing High Dynamic Range (HDR) environment maps and use the Precomputed Radiance Transfer (PRT) method for the global illumination computation. We leverage the PRT method to handle scenes with non-trivial topology represented by complex meshes. Also, we propose a hybrid of PRT and final gathering approach for high-quality rendering of objects with complex Bi-directional Reflectance Distribution Function (BRDF). We use this method for predictive rendering of the navigation LCD panel based on its measured BRDF. Since the global illumination computation leads to HDR images we propose a tone mapping algorithm tailored specifically for the CAVE. We employ head tracking to identify the observed screen region and derive for it proper luminance adaptation conditions, which are then used for tone mapping on all walls in the CAVE. We distribute our global illumination and tone mapping computation on all CPUs and CPUs available in the CAVE, which enables us to achieve interactive performance even for the costly final gathering approach.

In the paper, the influence of transmitter position accuracy on target localization in passive radar is investigated. The position of the transmitters used by the passive radar is often taken from public databases available on the Internet. This position may not be accurate, which will influence the process of target localization. The relationship between the error in the transmitter position and target localization is established in this paper. The analysis is based on linearization of the nonlinear relationships between the transmitter position and target localization.