Showing papers on "High-dynamic-range imaging published in 2015"

Robust High Dynamic Range Imaging by Rank Minimization

Abstract: This paper introduces a new high dynamic range (HDR) imaging algorithm which utilizes rank minimization. Assuming a camera responses linearly to scene radiance, the input low dynamic range (LDR) images captured with different exposure time exhibit a linear dependency and form a rank-1 matrix when stacking intensity of each corresponding pixel together. In practice, misalignments caused by camera motion, presences of moving objects, saturations and image noise break the rank-1 structure of the LDR images. To address these problems, we present a rank minimization algorithm which simultaneously aligns LDR images and detects outliers for robust HDR generation. We evaluate the performances of our algorithm systematically using synthetic examples and qualitatively compare our results with results from the state-of-the-art HDR algorithms using challenging real world examples.

Real-time noise-aware tone mapping

Abstract: Real-time high quality video tone mapping is needed for many applications, such as digital viewfinders in cameras, display algorithms which adapt to ambient light, in-camera processing, rendering engines for video games and video post-processing. We propose a viable solution for these applications by designing a video tone-mapping operator that controls the visibility of the noise, adapts to display and viewing environment, minimizes contrast distortions, preserves or enhances image details, and can be run in real-time on an incoming sequence without any preprocessing. To our knowledge, no existing solution offers all these features. Our novel contributions are: a fast procedure for computing local display-adaptive tone-curves which minimize contrast distortions, a fast method for detail enhancement free from ringing artifacts, and an integrated video tone-mapping solution combining all the above features.

High Dynamic Range Imaging

Abstract: High dynamic range (HDR) images and video contain pixels, which can represent much greater range of colors and brightness levels than that offered by existing, standard dynamic range images. Such “better pixels” greatly improve the overall quality of visual content, making it appear much more realistic and appealing to the audience. HDR is one of the key technologies of the future imaging pipeline, which will change the way the digital visual content is represented and manipulated. This article offers a broad review of the HDR methods and technologies with an introduction to fundamental concepts behind the perception of HDR imagery. It serves as both an introduction to the subject and a review of the current state of the art in HDR imaging. It covers the topics related to capture of HDR content with cameras and its generation with computer graphics methods; encoding and compression of HDR images and video; tone mapping for displaying HDR content on standard dynamic range displays; inverse tone mapping for upscaling legacy content for presentation on HDR displays; the display technologies offering HDR range; and finally image and video quality metrics suitable for HDR content. Keywords: high dynamic range imaging; tone mapping

Fuzzy fusion based high dynamic range imaging using adaptive histogram separation

Abstract: In this work, a high dynamic range (HDR) image generation method using a single input image is presented. The proposed approach generates over- and under-exposed images by making use of a novel adaptive histogram separation scheme. Thus, it becomes possible to eliminate ghosting effects which generally occur when several input image containing camera/object motion are utilized in HDR imaging. Additionally, it is proposed to utilize a fuzzy logic based approach at the fusion stage which takes visibility of the inputs pixels into account. Since the proposed approach is computationally light-weight, it is possible to implement it on mobile devices such as smart phones and compact cameras. Experimental results show that the proposed approach is able to provide ghost-free and improved HDR performance compared to the existing methods1.

Evaluation of Feature Detection in HDR Based Imaging Under Changes in Illumination Conditions

Abstract: High dynamic range (HDR) imaging enables to capture details in both dark and very bright regions of a scene, and is therefore supposed to provide higher robustness to illumination changes than conventional low dynamic range (LDR) imaging in tasks such as visual features extraction. However, it is not clear how much this gain is, and which are the best modalities of using HDR to obtain it. In this paper we evaluate the first block of the visual feature extraction pipeline, i.e., keypoint detection, using both LDR and different HDR-based modalities, when significant illumination changes are present in the scene. To this end, we captured a dataset with two scenes and a wide range of illumination conditions. On these images, we measure how the repeatability of either corner or blob interest points is affected with different LDR/HDR approaches. Our observations confirm the potential of HDR over conventional LDR acquisition. Moreover, extracting features directly from HDR pixel values is more effective than first tonemapping and then extracting features, provided that HDR luminance information is previously encoded to perceptually linear values.

Compression efficiency of HDR/LDR content

Abstract: High Dynamic Range (HDR) imaging is capable of delivering a wider range of luminance and color gamut compared to Standard Dynamic Range (SDR), offering to viewers a visual quality of experience close to that of real-life. In this study, we evaluate the quality of coded original HDR streams and HDR streams reconstructed from SDR videos and metadata, both compressed by the HEVC standard. Our evaluations have shown that the single HDR approach is largely preferred over the SDR counterpart.

High dynamic range imaging pipeline on the GPU

Abstract: Use of high dynamic range (HDR) images and video in image processing and computer graphics applications is rapidly gaining popularity. However, creating and displaying high resolution HDR content on CPUs is a time consuming task. Although some previous work focused on real-time tone mapping, implementation of a full HDR imaging (HDRI) pipeline on the GPU has not been detailed. In this article we aim to fill this gap by providing a detailed description of how the HDRI pipeline, from HDR image assembly to tone mapping, can be implemented exclusively on the GPU. We also explain the trade-offs that need to be made for improving efficiency and show timing comparisons for CPU versus GPU implementations of the HDRI pipeline.

Exposure bracketing via automatic exposure selection

Abstract: Exposure bracketing is widely used to generate high dynamic range (HDR) images. Exposure bracketing often consists of an image taken by the auto-exposure setting of a camera as well as two other images taken at ±n exposure levels away from the auto-exposure setting where n is manually selected or specified. The images in the bracket are then blended to generate an HDR image. This paper presents an automatic exposure selection method that relieves the user from setting the exposure level, thus allowing HDR images to be generated with no user intervention. This is achieved by using the camera characteristics function and the scene information. The results obtained indicate the HDR images generated by using this method outperform the manual selection of exposure level in terms of two widely used image quality measures.

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

Abstract: Digital imaging of natural scenes and optical phenomena present on them (such as shadows, twilights, and crepuscular rays) can be a very challenging task because of the range spanned by the radiances impinging on the capture system. We propose a novel method for estimating the set of exposure times (bracketing set) needed to capture the full dynamic range of a scene with high dynamic range (HDR) content. The proposed method is adaptive to scene content and to any camera response and configuration, and it works on-line since the exposure times are estimated as the capturing process is ongoing. Besides, it requires no a priori information about scene content or radiance values. The resulting bracketing sets are minimal in the default method settings, but the user can set a tolerance for the maximum percentage of pixel population that is underexposed or saturated, which allows for a higher number of shots if a better signal-to-noise ratio (SNR) in the HDR scene is desired. This method is based on the use of the camera response function that is needed for building the HDR radiance map by stitching together several differently exposed low dynamic range images of the scene. The use of HDR imaging techniques converts our digital camera into a tool for measuring the relative radiance outgoing from each point of the scene, and for each color channel. This is important for accurate characterization of optical phenomena present in the atmosphere while not suffering any loss of information due to its HDR. We have compared our method with the most similar one developed so far [IEEE Trans. Image Process.17, 1864 (2008)]. Results of the experiments carried out for 30 natural scenes show that our proposed method equals or outperforms the previously developed best approach, with less shots and shorter exposure times, thereby asserting the advantage of being adaptive to scene content for exposure time estimation. As we can also tune the balance between capturing time and the SNR in our method, we have compared its SNR performance against that of Barakat's method as well as against a ground-truth HDR image of maximum SNR. Results confirm the success of the proposed method in exploiting its tunability to achieve the desired balance of total Δt and SNR.

Bit-depth scalable lossless coding for high dynamic range images

Abstract: In this paper, we propose a bit-depth scalable lossless coding method for high dynamic range (HDR) images based on a reversible logarithmic mapping. HDR images are generally expressed as floating-point data, such as in the OpenEXR or RGBE formats. Our bit-depth scalable coding approach outputs base layer data and enhancement layer data. It can reconstruct the low dynamic range (LDR) image from the base layer data and reconstructs the HDR image by adding the enhancement layer data. Most previous two-layer methods have focused on the lossy coding of HDR images. Unfortunately, the extension of previous lossy methods to lossless coding does not significantly compress the enhancement layer data. This is because the bit depth becomes very large, especially for HDR images in floating-point data format. To tackle this problem, we apply a reversible logarithmic mapping to the input HDR data. Moreover, we introduce a format conversion to avoid any degradation in the quality of the reconstructed LDR image. The proposed method is effective for both OpenEXR and RGBE formats. Through a series of experiments, we confirm that the proposed method decreases the volume of compressed data while maintaining the visual quality of the reconstructed LDR images.

A Review On High-Dynamic-Range Imaging With Its Technique

Abstract: We presented a survey on High-dynamic-range imaging (HDRI or HDR) is a set of methods used in the imagingand photography to reproduce a superior dynamic range of luminosity than regular digital imaging or photographic methods can do. HDR images can denote a superior range of the luminance levels than can be attained using the extra 'classical' techniques. Images such as those holding many actual-world scenes, from same bright and direct sunlight to dangerous shade or very faint nebulae. It is the often succeeded in catching and then joining numerous dissimilar exposures of the similar subject matter. A Non-HDR cameras take a photograph with some limited amount of exposure range, as finally resulting in the damage of the detail in bright or dark parts. In this paper, we are studying about HDR image, generating of HDR image and also study about image fusion and methods of image fusioning.

A tone mapping operator based on neural and psychophysical models of visual perception

Abstract: High dynamic range imaging techniques involve capturing and storing real world radiance values that span many orders of magnitude. However, common display devices can usually reproduce intensity ranges only up to two to three orders of magnitude. Therefore, in order to display a high dynamic range image on a low dynamic range screen, the dynamic range of the image needs to be compressed without losing details or introducing artefacts, and this process is called tone mapping. A good tone mapping operator must be able to produce a low dynamic range image that matches as much as possible the perception of the real world scene. We propose a two stage tone mapping approach, in which the first stage is a global method for range compression based on a gamma curve that equalizes the lightness histogram the best, and the second stage performs local contrast enhancement and color induction using neural activity models for the visual cortex. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Implication of high dynamic range and wide color gamut content distribution

Abstract: High Dynamic Range (HDR) and Wider Color Gamut (WCG) content represents a greater range of luminance levels and a more complete reproduction of colors found in real-world scenes. The current video distribution environments deliver Standard Dynamic Range (SDR) signal. Therefore, there might be some significant implication on today's end-to-end ecosystem from content creation to distribution and finally to consumption. For SDR content, the common practice is to apply compression on Y'CbCr 4:2:0 using gamma transfer function and non-constant luminance 4:2:0 chroma subsampling. For HDR and WCG content, it is desirable to examine if such signal format still works well for compression, and it is interesting to know if the overall system performance can be further improved by exploring different signal formats and processing workflows. In this paper, we will provide some of our insight into those problems.

Method and Apparatus for Auto Exposure Value Detection for High Dynamic Range Imaging

Abstract: A method and apparatus for auto exposure value detection for High Dynamic Range (HDR) Imaging. An image can be captured as a captured image at a capture exposure. The exposure of a current iteration of the image can be changed by at least a fraction of an exposure value. A changed exposure image can be captured at the changed exposure value. A difference between an exposure data metric of the current iteration of the changed exposure image and an exposure data metric of a previous iteration of the image can be ascertained. The difference between the exposure data metric of the current iteration of the changed exposure image and the exposure data metric of the previous iteration of the image can be compared to a difference threshold. Changing the exposure value, capturing the changed exposure image, ascertaining the difference, and comparing the difference can be repeated when the difference between the exposure data metric of the current iteration of the changed exposure image and the exposure data metric of the previous iteration of the image exceeds the difference threshold.

Effects of display rendering on HDR image quality assessment

Abstract: High dynamic range (HDR) displays use local backlight modulation to produce both high brightness levels and large contrast ratios. Thus, the display rendering algorithm and its parameters may greatly affect HDR visual experience. In this paper, we analyze the impact of display rendering on perceived quality for a specific display (SIM2 HDR47) and for a popular application scenario, i.e., HDR image compression. To this end, we assess whether significant differences exist between subjective quality of compressed images, when these are displayed using either the built-in rendering of the display, or a rendering algorithm developed by ourselves. As a second contribution of this paper, we investigate whether the possibility to estimate the true pixel-wise luminance emitted by the display, offered by our rendering approach, can improve the performance of HDR objective quality metrics that require true pixel-wise luminance as input.

Single shot High Dynamic Range imaging using histogram separation and exposure fusion

Abstract: Conventionally, High Dynamic Range (HDR) images are generated by fusing multiple exposure Low Dynamic Range (LDR) images, where the HDR output often suffers from artifacts due to misalignment of camera and presence of dynamic objects in the scene. An efficient approach to overcome these issues is to use single shot HDR imaging. In this paper, we propose a method for generating an HDR image from a single LDR image. We first generate multiple exposures of the given scene using histogram separation by adopting varying bin sizes. The resulting LDR images are fused making use of the quality measures such as contrast, saturation and well - exposedness. The results show the effectiveness of the proposed approach which is verified qualitatively and in terms of various quantitative measures.

Evaluating the Color Fidelity of ITMOs and HDR Color Appearance Models

Abstract: With the increasing availability of high-dynamic-range (HDR) displays comes the need to remaster existing content in a way that takes advantage of the extended range of luminance and contrast that such displays offer. At the same time, it is crucial that the creative intent of the director is preserved through such changes as much as possible. In this article, we compare several approaches for dynamic range extension to assess their ability to correctly reproduce the color appearance of standard dynamic range (SDR) images on HDR displays. A number of state-of-the-art inverse tone mapping operators (ITMOs) combined with a standard chromatic adaptation transform (CAT) as well as some HDR color appearance models have been evaluated through a psychophysical study, making use of an HDR display as well as HDR ground-truth data. We found that global ITMOs lead to the most reliable performance when combined with a standard CAT, while more complex methods were found to be more scene dependent, and often less preferred than the unprocessed SDR image. HDR color appearance models, albeit being the most complete solutions for accurate color reproduction, were found to not be well suited to the problem of dynamic range expansion, suggesting that further research may be necessary to provide accurate color management in the context of inverse tone mapping.

Real-time visualization of low contrast targets from high-dynamic range infrared images based on temporal digital detail enhancement filter

Abstract: An image detail enhancement method to effectively visualize low contrast targets in high-dynamic range (HDR) infrared (IR) images is presented regardless of the dynamic range width. In general, high temperature dynamics from real-world scenes used to be encoded in a 12 or 14 bits IR image. However, the limitations of the human visual perception, from which no more than 128 shades of gray are distinguishable, and the 8-bit working range of common display devices make necessary an effective 12/14 bits HDR mapping into the 8-bit data representation. To do so, we propose to independently treat the base and detail image components that result from splitting the IR image using two dedicated guided filters. We also introduce a plausibility mask from which those regions that are prominent to present noise are accurately defined to be explicitly tackled to avoid noise amplification. The final 8-bit data representation results from the combination of the processed detail and base image components and its mapping to the 8-bit domain using an adaptive histogram-based projection approach. The limits of the histogram are accommodated through time in order to avoid global brightness fluctuations between frames. The experimental evaluation shows that the proposed noise-aware approach preserves low contrast details with an overall contrast enhancement of the image. A comparison with widely used HDR mapping approaches and runtime analysis is also provided. Furthermore, the proposed mathematical formulation enables a real-time adjustment of the global contrast and brightness, letting the operator adapt to the visualization display device without nondesirable artifacts.

Tone mapping for high-dynamic-range images using localized gamma correction

Abstract: Tone mapping methods aim to display a high-dynamic-range image on a common 8-bit liquid crystal display by compressing the dynamic range. We propose a simple but effective tone mapping operator (TMO) by using localized gamma correction. As the TMO involves the contrast and the color saturation components, our idea is to make use of gamma correction to adjust the values of these two components locally. The local weights can be determined according to the pixel values within local regions. Such an adaption can be handled more effectively for the contrast and color saturation in dark and bright regions of an image. Numerical examples are given to demonstrate the merit of the localized gamma correction scheme. The experiments reported in this paper illustrate that the proposed method can provide visually pleasing results, and it is also competitive with the other testing methods.

High dynamic range imaging method of camera array

Abstract: The invention discloses a high dynamic range imaging method of a camera array, and aims at solving the technical problem of low dynamic range of the existing camera array imaging method. According to the technical scheme, the method is that the maximum brightness and the minimum brightness of a target scene are obtained through a light meter or a built-in light detector in the camera so as to gain a group of optimized exposure bracketing grades; the camera combination participating in exposure in the array is determined, and the camera scene is synchronously shot through the camera combination so as to obtain a group of low dynamic range image containing different exposure settings of the target scene; the group of low dynamic range images is geometrically corrected according to the geometric relationship between the camera layout and the target scene to obtain a group of corrected low dynamic range images which cover the target scene dynamic range. According to the method, the total exposure time, of using the multi-exposure technology to obtain the high dynamic range image, which is equal to the sum of the times of a plurality of exposure, is reduced to the longest exposure time of the exposure bracketing combination; the problems of large time consumption due to exposing the static scene high dynamic range at a plurality of times and ghosting of imaging of the dynamic scene high dynamic range can be solved.

Ghost-free high dynamic range imaging via moving objects detection and extension

Abstract: High dynamic range imaging(HDRI) techniques are proposed to synthesize high dynamic range (HDR) images from multi-exposure images. However, ghost artifacts may appear if images are synthesized directly when there are moving objects in the scene. This paper presents an algorithm to composite a HDR image from multi-exposure images without ghost artifacts. To remove the ghosts in the final image, the proposed algorithm firstly produces a 0–1 map based on a Markov Random Field(MRF) framework. The moving areas are detected and marked with 1. Then, moving areas are extended and used in the final exposure fusion step. The marked pixels are assigned zero weights to prevent ghost artifacts.

Imaging system and method for concurrent multiview multispectral polarimetric light-field high dynamic range imaging

Abstract: There is disclosed a novel system and method for multiview, multispectral, polarimetric, light-field, and high dynamic range imaging in a concurrent manner specifically capturing information at different spectral bands and light polarizations simultaneously. The present system and method is capable of ( 1 ) concurrent imaging of multiple spectral bands (including spectral bands beyond the visible region of the electromagnetic spectrum), proportional or greater than the number of filters used in the device, ( 2 ) concurrent imaging of multiple light polarizations (Stokes vectors), ( 3 ) acquiring images at different point-of-view of the same scene and/or object that allow for topographical reconstruction, ( 4 ) concurrent imaging of the multiple depth of fields that allow for light-field imaging, and ( 5 ) concurrent imaging of multiple simulated exposures of the detector that allow for high dynamic range imaging, all at the same time using a single sensor in the same imaging system enclosure.

HDR image encoding using reconstruction functions based on piecewise linear approximations

Abstract: Two-layer encoding schemes for HDR images can not only reduce the storage requirements, but more importantly they can also ensure backward compatibility as imaging technology makes the transition from LDR to HDR. In this paper, we present a two-layer lossy encoding scheme for HDR images, which models each channel of the HDR image as a piecewise linear function of its tone-mapped version, to reduce the dynamic range of the residual image and achieve a better compression. The tone-mapped image and the residual image for each channel are saved as two separate LDR images, and these along with the piecewise linear models, encode the details of the HDR image. The encoded images are compatible to both HDR and non-HDR enabled devices for visualization and processing. Detailed comparison with similar existing state of the art two-layer techniques is presented to show the effectiveness of our proposed scheme.

HDR image noise estimation for denoising tone mapped images

Abstract: Tone mapping operators are designed to compress the dynamic range of high dynamic range (HDR) images while preserving the perceived image brightness, but they often enhance image noise in the process, specially in low-light conditions. We propose a method for reducing noise in images created by any tone mapping operator. Our approach leverages the noise distribution of the HDR image to guide the range kernel of a cross bilateral filter that is used to denoise the tone mapped image. When the noise distribution is unknown, we use a new method to automatically estimate it assuming that the HDR image was produced as an average of multiple exposures taken in RAW or JPEG compressed format. Our method performs quantitatively better than existing denoising methods applied on either the original HDR or the tone-mapped images directly, and a user study confirms that it produces visually preferable results.

Democratic Tone Mapping Using Optimal K-means Clustering

Abstract: The field of high dynamic range imaging addresses the problem of capturing and displaying the large range of luminance levels found in the world, using devices with limited dynamic range. In this paper we present a novel tone mapping algorithm that is based on \(K\)-means clustering. Using dynamic programming we are able to, not only solve the clustering problem efficiently, but also find the global optimum. Our algorithm runs in \(O(N^2K)\) for an image with \(N\) luminance levels and \(K\) output levels. We show that our algorithm gives comparable result to state-of-the-art tone mapping algorithms, but with the additional large benefit of a total lack of parameters. We test our algorithm on a number of standard high dynamic range images, and give qualitative comparisons to a number of state-of-the-art tone mapping algorithms.

Illuminance-proxy high dynamic range imaging: a simple method to measure surface reflectance

Abstract: A technique to measure arbitrarily complex patterns of diffuse surface reflectance under real-world illumination conditions is presented. The technique is founded on high dynamic range (HDR) imaging whereby the luminance values in an HDR image are used to derive average and/or per-pixel values of surface reflectance. Two variants of the method are described and the results from both are compared with analytical solutions. Whilst the technique has general application for the measurement of reflectance, the authors make the case that there is a pressing need to survey occupied building spaces since the notional/typical reflectance values commonly employed in simulation for compliance testing may be quite different from those found in real buildings.

Luminance-Based Measures of Contour Distinctness of 3D Objects as a Component of Light Modeling

Abstract: This article presents possible luminance-based measures of contour distinctness of 3D objects observed under real daylight conditions. Contour distinctness is considered here as a component of the broader concept of light modeling and is a significant metric of quality lighting. We set up an experiment where different measures of contour distinctness were studied with the help of high dynamic range imaging techniques. Measures obtained from the luminance maps were brought into correlation with survey results from 32 subjects. The analytical comparison showed that the contrast measurement (calculated with the Weber formula), luminance ratio between average luminance of the object and average luminance of the background, mean of paired point luminance ratio (mean point LR) measurements around the contour of the object, and percentage of the invisible part of the contour are good predictors for contour distinctness of the observed 3D objects. The proposed measures expressed in numerical values are co...

High dynamic range image acquisition method using proportion integration differentiation controller

Abstract: The extensive application of surface mount technology requires various measurement methods to evaluate the printed circuit board (PCB), and visual inspection is one critical method. The local oversaturation, arising from the nonconsistent reflectivity of the PCB surface, will lead to an erroneous result. This paper presents a study on a high dynamic range image (HDRI) acquisition system which can capture HDRIs with less local oversaturation. The HDRI system is composed of the liquid crystal on silicon (LCoS) and charge-coupled diode (CCD) sensor. In this system, the LCoS uses a negative feedback to extend the dynamic range of the system, and the proportion integration differentiation (PID) theory is used to control the system for its rapidity. The input of the PID controller is images captured by the CCD sensor and the output is the LCoS mask, which controls the LCoS’s reflectivity. The significant characteristics of our method are that the PID control can adjust the image brightness pixel to pixel and the feedback procedure is accomplished by the computer in less time than the traditional method. Experimental results demonstrate that the system could capture HDRIs with less local oversaturation.

High Dynamic Range Imaging By Perceptual Logarithmic Exposure Merging

Abstract: In this paper we emphasize a similarity between the logarithmic type image processing LTIP model and the Naka-Rushton model of the human visual system HVS. LTIP is a derivation of logarithmic image processing LIP, which further replaces the logarithmic function with a ratio of polynomial functions. Based on this similarity, we show that it is possible to present a unifying framework for the high dynamic range HDR imaging problem, namely, that performing exposure merging under the LTIP model is equivalent to standard irradiance map fusion. The resulting HDR algorithm is shown to provide high quality in both subjective and objective evaluations.

Is there a preference for linearity when viewing natural images

Abstract: The system gamma of the imaging pipeline, defined as the product of the encoding and decoding gammas, is typically greater than one and is stronger for images viewed with a dark background (e.g. cinema) than those viewed in lighter conditions (e.g. office displays). 1-3 However, for high dynamic range (HDR) images reproduced on a low dynamic range (LDR) monitor, subjects often prefer a system gamma of less than one, 4 presumably reflecting the greater need for histogram equalization in HDR images. In this study we ask subjects to rate the perceived quality of images presented on a LDR monitor using various levels of system gamma. We reveal that the optimal system gamma is below one for images with a HDR and approaches or exceeds one for images with a LDR. Additionally, the highest quality scores occur for images where a system gamma of one is optimal, suggesting a preference for linearity (where possible). We find that subjective image quality scores can be predicted by computing the degree of histogram equalization of the lightness distribution. Accordingly, an optimal, image dependent system gamma can be computed that maximizes perceived image quality.