Dynamic Range Images Research Articles

23‐3: A Histogram based Method for Dynamic Range Expansion

A method for Dynamic Range expansion is presented with its FPGA solution. This can help us converting a Low Dynamic Range image to a High Dynamic Range one. So that we can use more available brightness levels of display panel and see unseen details of images.

TOWARDS RADIOMETRICAL ALIGNMENT OF 3D POINT CLOUDS

Abstract. 3D laser scanners are typically not able to collect color information. Therefore coloring is often done by projecting photos of an additional camera to the 3D scans. The capturing process is time consuming and therefore prone to changes in the environment. The appearance of the colored point cloud is mainly effected by changes of lighting conditions and corresponding camera settings. In case of panorama images these exposure variations are typically corrected by radiometrical aligning the input images to each other. In this paper we adopt existing methods for panorama optimization in order to correct the coloring of point clouds. Therefore corresponding pixels from overlapping images are selected by using geometrically closest points of the registered 3D scans and their neighboring pixels in the images. The dynamic range of images in raw format allows for correction of large exposure differences. Two experiments demonstrate the abilities of the approach.

An improved schlieren method for measurement and automatic reconstruction of the far-field focal spot.

The schlieren method of measuring far-field focal spots offers many advantages at the Shenguang III laser facility such as low cost and automatic laser-path collimation. However, current methods of far-field focal spot measurement often suffer from low precision and efficiency when the final focal spot is merged manually, thereby reducing the accuracy of reconstruction. In this paper, we introduce an improved schlieren method to construct the high dynamic-range image of far-field focal spots and improve the reconstruction accuracy and efficiency. First, a detection method based on weak light beam sampling and magnification imaging was designed; images of the main and side lobes of the focused laser irradiance in the far field were obtained using two scientific CCD cameras. Second, using a self-correlation template matching algorithm, a circle the same size as the schlieren ball was dug from the main lobe cutting image and used to change the relative region of the main lobe cutting image within a 100×100 pixel region. The position that had the largest correlation coefficient between the side lobe cutting image and the main lobe cutting image when a circle was dug was identified as the best matching point. Finally, the least squares method was used to fit the center of the side lobe schlieren small ball, and the error was less than 1 pixel. The experimental results show that this method enables the accurate, high-dynamic-range measurement of a far-field focal spot and automatic image reconstruction. Because the best matching point is obtained through image processing rather than traditional reconstruction methods based on manual splicing, this method is less sensitive to the efficiency of focal-spot reconstruction and thus offers better experimental precision.

Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting

Precision agriculture is gaining an increasing interest in the current farming paradigm. This new production concept relies on the use of information technology (IT) to provide a control and supervising structure that can lead to better management policies. In this framework, imaging techniques that provide visual information over the farming area play an important role in production status monitoring. As such, accurate representation of the gathered production images is a major concern, especially if those images are used in detection and classification tasks. Real scenes, observed in natural environment, present high dynamic ranges that cannot be represented by the common LDR (Low Dynamic Range) devices. However, this issue can be handled by High Dynamic Range (HDR) images since they have the ability to store luminance information similarly to the human visual system. In order to prove their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was carried out. The obtained results show that the use of HDR images improves the detection performance to more than 30% when compared to LDR.

Compressive dynamic range imaging via Bayesian shrinkage dictionary learning

We apply the Bayesian shrinkage dictionary learning into compressive dynamic-range imaging. By attenuating the luminous intensity impinging upon the detector at the pixel level, we demonstrate a conceptual design of an 8-bit camera to sample high-dynamic-range scenes with a single snapshot. Coding strategies for both monochrome and color cameras are proposed. A Bayesian reconstruction algorithm is developed to learn a dictionary in situ on the sampled image, for joint reconstruction and demosaicking. We use global-local shrinkage priors to learn the dictionary and dictionary coefficients representing the data. Simulation results demonstrate the feasibility of the proposed camera and the superior performance of the Bayesian shrinkage dictionary learning algorithm.

A model of perceived dynamic range for HDR images

For High Dynamic Range (HDR) content, the dynamic range of an image is an important characteristic in algorithm design and validation, analysis of aesthetic attributes and content selection. Traditionally, it has been computed as the ratio between the maximum and minimum pixel luminance, a purely objective measure; however, the human visual system's perception of dynamic range is more complex and has been largely neglected in the literature. In this paper, a new methodology for measuring perceived dynamic range (PDR) of chromatic and achromatic HDR images is proposed. PDR can benefit HDR in a number of ways: for evaluating inverse tone mapping operators and HDR compression methods; aesthetically; or as a parameter for content selection in perceptual studies. A subjective study was conducted on a data set of 36 chromatic and achromatic HDR images. Results showed a strong agreement across participants' allocated scores. In addition, a high correlation between ratings of the chromatic and achromatic stimuli was found. Based on the results from a pilot study, five objective measures (pixel-based dynamic range, image key, area of bright regions, contrast and colorfulness) were selected as candidates for a PDR predictor model; two of which have been found to be significant contributors to the model. Our analyses show that this model performs better than individual metrics for both achromatic and chromatic stimuli.

Verification of the Accuracy of the Luminance-Based Metrics of Contour, Shape, and Detail Distinctness of 3D Object in Simulated Daylit Scene by Numerical Comparison with Photographed HDR Images

ABSTRACTThis study verifies the accuracy of previously developed luminance-based metrics of light modeling (that is, the distinctness of contour, shape, and details of daylit 3D objects) through comparison of numerical values of the metrics obtained from photographed and simulated high dynamic range (HDR) images. The analysis of the luminance data of eight photographed and eight simulated HDR images of Venetian masks showed that the mean relative error of all tested metrics was 14.78%. The minimum average relative error was 7.91%, and the maximum error (found for only one metric) was 27.75%. The glossy objects had higher error rates than matte objects tested within the experiment. Additionally, the variation among luminance-based metrics obtained from simulated and photographed HDR images was compared with variation among illuminance-based metrics. It became evident that luminance-based metrics (consequently color and specularity dependent) showed considerable variation among examined masks, affirming the impact of color and specularity on visibility of contour, shape, and detail. Though the tested luminance-based metrics may need further investigation in experimental conditions that differ from those used in this study, it is clear that they could be applied both with photographed and simulated luminance maps with precision of about 15%. Experimental results confirm the robustness of the metrics and encourage use of the luminance-based light modeling metrics in computer lighting simulations.

Concept of proton radiography using energy resolved dose measurement

Energy resolved dosimetry offers a potential path to single detector based proton imaging using scanned proton beams. This is because energy resolved dose functions encrypt the radiological depth at which the measurements are made. When a set of predetermined proton beams ‘proton imaging field’ are used to deliver a well determined dose distribution in a specific volume, then, at any given depth x of this volume, the behavior of the dose against the energies of the proton imaging field is unique and characterizes the depth x. This concept applies directly to proton therapy scanning delivery methods (pencil beam scanning and uniform scanning) and it can be extended to the proton therapy passive delivery methods (single and double scattering) if the delivery of the irradiation is time-controlled with a known time-energy relationship.To derive the water equivalent path length (WEPL) from the energy resolved dose measurement, one may proceed in two different ways. A first method is by matching the measured energy resolved dose function to a pre-established calibration database of the behavior of the energy resolved dose in water, measured over the entire range of radiological depths with at least 1 mm spatial resolution. This calibration database can also be made specific to the patient if computed using the patient x-CT data. A second method to determine the WEPL is by using the empirical relationships between the WEPL and the integral dose or the depth at 80% of the proximal fall off of the energy resolved dose functions in water.In this note, we establish the evidence of the fundamental relationship between the energy resolved dose and the WEPL at the depth of the measurement. Then, we illustrate this relationship with experimental data and discuss its imaging dynamic range for 230 MeV protons.

Embedded processing methods for online visual analysis of laser welding

Online monitoring and closed-loop control of laser welding offer great possibilities for achieving better weld quality. Earlier work on visual laser welding monitoring has mainly focused on aluminum and fairly thin steel used, for example, in car production. We extend this work by focusing on the automated analysis of the phenomena present in the laser welding of thick steel, where all of the phenomena related to the weld quality are still not well understood or controlled. This paper presents the implementation, test results and analysis for weld monitoring methods implemented on a compact smart camera system. The applied embedded sensor–processor platform allows for high-speed implementation of image capture and dynamic range compression, real-time seam tracking and spatter feature extraction. The paper describes experimental results from implemented real-time algorithms for seam tracking and spatter extraction and additional off-line analysis of methods for spatter tracking and seam widening detection, which are also feasible for future online hardware implementation. The results suggest that it is possible to integrate a compact laser welding analysis system, which achieves analysis rates that are sufficient for real-time process control.

Extended Image Dynamic Range System for UHDTV Broadcasting

Japan Broadcasting Corporation (NHK) has been developing 8 K Super Hi-Vision (SHV), a member of ultra-high-definition television (UHDTV). This can provide an increased sense of presence and realness to viewers. 8 K SHV has system parameters of 7680 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math></inline-formula> 4320 pixels, 120 Hz frame frequency, and wide color gamut. With the addition of an extended image dynamic range feature, it is expected that 8 K SHV can be further enhanced to become the true ultimate TV system. We first discuss requirements for extended image dynamic range TV systems. Then, we propose the essential system parameter values based on the requirements. We introduce the specific parameter of video level corresponding to reference white to address highlights specifically. The proposed system parameters are designed with consideration of compatibility with existing workflows and infrastructure. We conducted an experiment to examine the influence of peak display luminance level on picture production and confirmed that production practices should be substantially changed to fully exploit the display capabilities of the increased luminance levels. We also conducted experiments to determine the required conditions of black level and peak luminance level of displays in various viewing environments.

Real-time high dynamic range laser scanning microscopy.

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Terrain mapping under extreme light conditions with direct stereo matching method through aggregating matching costs by weight

One of the biggest problems in applying stereo vision techniques in field robotics is how to acquire 3D terrain maps under extreme light conditions. Through multiple exposures, the dynamic range of images can be increased. In this paper, instead of using existing lighting enhancement methods such as exposure fusion to increase the texture of 2D image, we propose that the matching costs of the images grabbed with multiple exposures are directly summed by weight. Compared with the previous methods such as exposure fusion, with the proposed method, it is not necessary to fuse the 2D images captured with multiple exposures, and for each pixel of the matching image, the local information in its local window can be better retained. Since it is possible that the camera is moved between exposures when the images are grabbed, the images captured with multiple exposures are aligned to the image acquired with auto exposure. In order to evaluate the performance of the proposed method, two different stereo matching algorithms were used: a local window-based method and semi-global method. Through experiments in laboratory and outdoors with a stereo vision camera fixed on a tripod and held in the hand, it was verified that the proposed method consistently allowed more valid points to be obtained and the 3D model of terrain can be built more accurately. Especially when the local window-based method was used, the proposed method performed much better.

Monitoring and rendering of visual and photo-biological properties of daylight-redirecting systems

We previously developed a Camera-Like Light Sensor (CLLS) to record images using a novel High Dynamic Range (HDR) imaging vision sensor. The device was equipped with customized filters for adapting the camera’s spectral sensitivity to both photopic and circadian sensitivities. Here, we aim at investigating photometric and circadian metrics to assess and simulate the potential of light on non-visual functions. The CLLS was used to monitor luminance and circadian weighted radiance (Lec) over time in two test rooms, equipped with different daylight re-directing devices: venetian blinds (VB) and optical louver systems (OLS). Additionally, a computer simulation was performed for the two test rooms using the software RADIANCE: false colour images were used to demonstrate distribution of luminance and absolute values of Lec. Circadian weighted irradiance (Eec) was also computed at different positions corresponding to the gaze directions of a seated office worker. From our results, the VB provided overall higher illuminance compared to the OLS, but when a virtually seated observer was facing desk, the OLS provided larger circadian weighted irradiance in the afternoon. Our results illustrate the use of simulations for circadian metrics, which will be applicable in the future to predict the potential impact of light on non-visual functions for daylighting optimization in buildings.

HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter.

Pathological image enhancement is a significant topic in the field of pathological image processing. This paper proposes a high dynamic range (HDR) pathological image enhancement method based on improved bias field correction and guided image filter (GIF). Firstly, a preprocessing including stain normalization and wavelet denoising is performed for Haematoxylin and Eosin (H and E) stained pathological image. Then, an improved bias field correction model is developed to enhance the influence of light for high-frequency part in image and correct the intensity inhomogeneity and detail discontinuity of image. Next, HDR pathological image is generated based on least square method using low dynamic range (LDR) image, H and E channel images. Finally, the fine enhanced image is acquired after the detail enhancement process. Experiments with 140 pathological images demonstrate the performance advantages of our proposed method as compared with related work.

A Novel Enhancement Algorithm Combined with Improved Fuzzy Set Theory for Low Illumination Images

A novel enhancement method of global brightness modulation and local contrast enhancement combined with the improved fuzzy set theory is proposed for color image contrast enhancement. The proposed method consists of three stages. Firstly, putting forward nonlinear global brightness mapping model adjusts dynamic range of images for luminance componentVofHSVcolor space. Secondly, membership function is established in stages to adjust local contrast of image details nonlinearly based on fuzzy set theory. Finally, the enhanced images are transformed fromHSVcolor space intoRGBcolor space. The experiments further show that the proposed method has the shortest processing time, the highest AIC values, and the least NIQE values among the other four conventional methods. It has excellent effect, which can enhance the global brightness and local contrast, and advance visibility of low illumination images.

HIGH DYNAMIC RANGE IMPLEMENTATION ON ACUTE LEUKEMIA SLIDE IMAGES

Conventional diagnosis of acute leukemia is based on examining the morphology of the blood and bone marrow smear under the microscope and the process can be tedious, time intensive and highly skilled resources dependent. Over recent years, features fusion techniques base on statistical and morphological features had been explored in computer vision studies to enhance the capability of acute leukemia diagnosis task. However, microscopic image capture from the light microscope usually has poor quality due to the limited dynamic range of the camera. Thus, image regions with intensity levels outside the dynamic range captured by the camera sensor suffer from lack of details, appearing either underexposed or overexposed. This paper proposed a High Dynamic Range (HDR) imaging techniques to solve the problem of limited dynamic range and enhance the morphological features of blast cells. The proposed method consists of two main parts: implementing HDR techniques on acute leukemia slide images and comparing the dynamic range between HDR image and original images with different exposure time based on the intensity histograms obtained. The results presented showed that the HDR implementation has enhanced the morphological features of blast cells and increase the dynamic range, hence may benefit in the feature extraction and classification process of acute leukemia.

Evaluation of Various Tone Mapping Operators for Backward Compatible JPEG Image Coding

Recently, the standardization of backward compatible JPEG image coding for high dynamic range (HDR) image has been undertaken to establish an international standard called “JPEG XT.” The JPEG XT consists of two layers: the base layer and the residual layer. The base layer contains tone mapped low dynamic range (LDR) image data and the residual layer contains the error signal used to reconstruct the HDR image. This paper gives the result of a study to evaluate the overall performance of tone mapping operators (TMOs) for this standard. The evaluation is performed using five HDR image datasets and six TMOs for profiles A, B, and C of the proposed JPEG XT standard. The Tone Mapped image Quality Index (TMQI) and no reference image quality assessment (NR IQA) are used for measuring the LDR image quality. The peak signal to noise ratio (PSNR) is used to evaluate the overall compression performance of JPEG XT profiles A, B, and C. In TMQI and NR IQA measurements, TMOs using display adaptive tone mapping and adaptive logarithmic mapping each gave good results. A TMO using adaptive logarithmic mapping gave good PSNRs.

Modeling a color-rendering operator for high dynamic range images using a cone-response function

Tone-mapping operators are the typical algorithms designed to produce visibility and the overall impression of brightness, contrast, and color of high dynamic range (HDR) images on low dynamic range (LDR) display devices. Although several new tone-mapping operators have been proposed in recent years, the results of these operators have not matched those of the psychophysical experiments based on the human visual system. A color-rendering model that is a combination of tone-mapping and cone-response functions using an XYZ tristimulus color space is presented. In the proposed method, the tone-mapping operator produces visibility and the overall impression of brightness, contrast, and color in HDR images when mapped onto relatively LDR devices. The tone-mapping resultant image is obtained using chromatic and achromatic colors to avoid well-known color distortions shown in the conventional methods. The resulting image is then processed with a cone-response function wherein emphasis is placed on human visual perception (HVP). The proposed method covers the mismatch between the actual scene and the rendered image based on HVP. The experimental results show that the proposed method yields an improved color-rendering performance compared to conventional methods.

Bowtie filters for dedicated breast CT: Analysis of bowtie filter material selection.

For a given bowtie filter design, both the selection of material and the physical design control the energy fluence, and consequently the dose distribution, in the object. Using three previously described bowtie filter designs, the goal of this work is to demonstrate the effect that different materials have on the bowtie filter performance measures. Three bowtie filter designs that compensate for one or more aspects of the beam-modifying effects due to the differences in path length in a projection have been designed. The nature of the designs allows for their realization using a variety of materials. The designs were based on a phantom, 14 cm in diameter, composed of 40% fibroglandular and 60% adipose tissue. Bowtie design #1 is based on single material spectral matching and produces nearly uniform spectral shape for radiation incident upon the detector. Bowtie design #2 uses the idea of basis-material decomposition to produce the same spectral shape and intensity at the detector, using two different materials. With bowtie design #3, it is possible to eliminate the beam hardening effect in the reconstructed image by adjusting the bowtie filter thickness so that the effective attenuation coefficient for every ray is the same. Seven different materials were chosen to represent a range of chemical compositions and densities. After calculation of construction parameters for each bowtie filter design, a bowtie filter was created using each of these materials (assuming reasonable construction parameters were obtained), resulting in a total of 26 bowtie filters modeled analytically and in the penelope Monte Carlo simulation environment. Using the analytical model of each bowtie filter, design profiles were obtained and energy fluence as a function of fan-angle was calculated. Projection images with and without each bowtie filter design were also generated using penelope and reconstructed using FBP. Parameters such as dose distribution, noise uniformity, and scatter were investigated. Analytical calculations with and without each bowtie filter show that some materials for a given design produce bowtie filters that are too large for implementation in breast CT scanners or too small to accurately manufacture. Results also demonstrate the ability to manipulate the energy fluence distribution (dynamic range) by using different materials, or different combinations of materials, for a given bowtie filter design. This feature is especially advantageous when using photon counting detector technology. Monte Carlo simulation results from penelope show that all studied material choices for bowtie design #2 achieve nearly uniform dose distribution, noise uniformity index less than 5%, and nearly uniform scatter-to-primary ratio. These same features can also be obtained using certain materials with bowtie designs #1 and #3. With the three bowtie filter designs used in this work, the selection of material is an important design consideration. An appropriate material choice can improve image quality, dose uniformity, and dynamic range.

Low‐cost and high‐speed hardware implementation of contrast‐preserving image dynamic range compression for full‐HD video enhancement

This study presents a cost-efficient and high-performance field programmable gate array (FPGA)-based hardware implementation of a contrast-preserving image dynamic range compression algorithm, which is an important function used in modern digital video cameras and displays to improve visual quality of standard dynamic range colour images (8 bits/channel). To achieve this purpose, a hardware-friendly approximation to an existing fast dynamic range compression with local contrast preservation (FDRCLCP) algorithm is proposed. The computation of the proposed approximated FDRCLCP algorithm requires only fixed-point unsigned binary addition, multiplication, and bit-shifting. Moreover, the proposed hardware implementation uses a line buffer instead of a frame buffer to process whole image data. These advantages significantly improve throughput performance and reduce memory requirement of the system. The FPGA implementation of the proposed algorithm requires only about 98 K bits on-chip memory and achieves about 170.24 MHz operating frequency by using an Altera Cyclone II device. This is a large improvement compared with the existing results as it is quick enough to process full high-definition videos (1920 × 1080 pixels) at least 80 frames per second using a low-cost FPGA device.