Deep Tone Mapping Operator for High Dynamic Range Images.

Tone-mapping-operators (TMOs) provide a useful means for converting high dynamic range (HDR) images to low dynamic range (LDR) images so that they can be viewed on standard displays, but this may influence the visual quality of experience (QoE) of the end-user. There is a need to understand the impact of TMOs to inform the choice of TMO algorithms for different displays, especially for small-screen-devices (SSDs) such as those used in mobile phones. This is important, as mobile devices are becoming the primary means of consuming multimedia contents. However, few studies have been undertaken to assess the impact of TMOs and viewing devices (especially SSDs) on the visual QoE of the user when using. In this chapter, we evaluate subjectively and objectively, the commonly used TMOs in different displays and resolutions for colour and grey-scale HDR images. Our results show that viewing devices have an influence on the TMOs performance, suggesting the need for a careful choice of TMO to enhance the viewing-QoE of the end-user. As expected, the higher resolution, the better HDR-image quality. Surprisingly, there was no significant difference between the Mean of Opinion Score (MOS) scores for colour and grey-scale images in SSDs. The device and TMOs affect QoE for colour and grey HDR-image equally. We found Shannon entropy (SE) to be a good objective measure of quality for colour and grey HDR images, suggesting that entropy may find use in automated HDR quality control assessment schemes, while; HDR-VDP-2 is a good objective measure for colour HDR image only.

A fixed-point tone mapping operation (TMO) instead of a floating-point TMO is proposed in this paper. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image. Since pixel values of an HDR image are generally expressed in a floating-point data format, e.g. RGBE and OpenEXR, a TMO is also implemented in floating-point arithmetic in conventional approaches. However, it requires a huge computational cost, even though a resulting LDR image is expressed in simple integers. The proposed TMO is implemented with only fixed-point arithmetic. As a result, the proposed method reduces a computational cost. Experimental results shows the PSNR of LDR images in the proposed method are comparable to those of the conventional methods.

International audience

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.

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

High dynamic range (HDR) images are becoming pervasive due to capturing or rendering of a wider range of luminance, but their special display equipment is difficult to be popularized because of high cost and technological problem. Thus, HDR images must be adapted to the conventional display devices by applying tone mapping (TM) operation, which puts forward higher requirements for intellectual property protection of HDR images. As the robustness presents regional diversity in the low dynamic range (LDR) watermarked image after TM, which is different from the traditional watermarking technologies, a concept of watermarking activity is defined and used to distinguish the essential distinction of watermarking between LDR image and HDR image in this paper. Then, a novel robust HDR image watermarking algorithm is proposed against TM operations. Firstly, based on the hybrid processing of redundant discrete wavelet transform and singular value decomposition, the watermark is embedded by modifying the structure information of the HDR image. Distinguished from LDR image watermarking, the high embedding strength can cause more obvious distortion in the high brightness regions of HDR image than the low brightness regions. Thus, a perceptual brightness mask with low complexity is designed to improve the imperceptibility further. Experimental results show that the proposed algorithm is robust to the existing TM operations, with taking into account the imperceptibility and embedded capacity, which is superior to the current state-of-art HDR image watermarking algorithms.

A number of successful tone mapping operators for contrast compression have been proposed due to the need to visualize high dynamic range (HDR) images on low dynamic range devices. They were inspired by fields as diverse as image processing, photographic practice, and modeling of the human visual systems (HVS). The variety of approaches calls for a systematic perceptual evaluation of their performance. We conduct a psychophysical experiment based on a direct comparison between the appearance of real-world scenes and HDR images of these scenes displayed on a low dynamic range monitor. In our experiment, HDR images are tone mapped by seven existing tone mapping operators. The primary interest of this psychophysical experiment is to assess the differences in how tone mapped images are perceived by human observers and to find out which attributes of image appearance account for these differences when tone mapped images are compared directly with their corresponding real-world scenes rather than with each other. The human subjects rate image naturalness, overall contrast, overall brightness, and detail reproduction in dark and bright image regions with respect to the corresponding real-world scene. The results indicate substantial differences in perception of images produced by individual tone mapping operators. We observe a clear distinction between global and local operators in favor of the latter, and we classify the tone mapping operators according to naturalness and appearance attributes.

This paper proposes a High Dynamic Range (HDR) image Tone Mapping (TM) approach converting HDR images into Low Dynamic Range (LDR) images so as the tone mapped HDR images ensure good visual quality on LDR display devices in accordance with the observers’ assessment. The proposed algorithm adjusts the logarithm luminance distribution of the HDR image according to a perceptual quantizer with respect to the Human Visual System (HVS) using a piecewise linear function. The parameters’s approximation are induced by L M -norms (l 1 , l 2 , l ∞ ) and the performance of the proposed algorithm is discussed. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches.

In this paper we present a new technique for the display of High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as reference, that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO.

In this work, we proposed a novel depth adaptive tone mapping scheme for stereo HDR imaging and 3D display. We are interested in the case where different exposures are taken from different viewpoints. The scheme employed a new depth-adaptive cross-trilateral filter (DA-CTF) for recovering High Dynamic Range (HDR) images from multiple Low Dynamic Range (LDR) images captured at different exposure levels. Explicitly leveraging additional depth information in the tone mapping operation correctly identify global contrast change and detail visibility change by preserving the edges and reducing halo artifacts in the synthesized 3D views by depth-image-based rendering (DIBR) procedure. The experiments show that the proposed DA-CTF and DIBR scheme outperforms state-of-the-art operators in the enhanced depiction of tone mapped HDR stereo images on LDR displays.

The present paper proposes a blind multi-bit watermarking method for High Dynamic Range (HDR) images. The proposed approach is designed in order to guarantee the watermark imperceptibility both in the HDR marked image and in its Low Dynamic Range (LDR) counterpart, being thus robust against significant non-linear distortions such as those performed by tone-mapping operators (TMOs). In order to do so, the wavelet transform of the Just Noticeable Difference (JND)- scaled space of the original HDR image is employed as embedding domain. Moreover, a visual mask taking into account specific aspects of the Human Visual System (HVS) is exploited to improve the quality of the resulting watermarked image. Specifically, bilateral filtering is used to locate information on the detail part of the HDR image, where the watermark should be preferably embedded. A contrast sensitivity function is also employed to modulate the watermark intensity in each wavelet decomposition subband according to its scale and orientation. An extensive set of experimental results testifies the effectiveness of the proposed scheme in embedding multi-bit watermarks into HDR images without affecting the visual quality of the original image, while being robust against TMOs.

This paper addresses the conversion problem of High Dynamic Range (HDR) images into Low Dynamic Range (LDR) images. The aim of this conversion is to ensure a good visual rendering of the displayed Tone Mapped (TM) HDR images in accordance with the observers' assessment. To do so, the proposed algorithm adjusts a piecewise linear function to the logarithm luminance distribution of the HDR image to adapt this transformation to the perceptual quantizer in accordance with the Human Visual System (HVS). The computation of the slope value of the piecewise linear transformation is simplified. Indeed, it is given by the ratio between the probability and the logarithm luminance distance in the sampling bin. This leads to histograms which tend to be flat, thus inducing a contrast enhancement of the tone mapped HDR images in both under-exposed and overexposed areas. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches.

We propose an integer tone mapping operator (TMO) for high dynamic range (HDR) images expressed in a floating-point data format. Two purposes are achieved by the proposed TMO. The first purpose is to implement a TMO with less memory space. The second purpose is to give an important step to realize a fixed-point TMO. The proposed TMO is available for HDR images in the OpenEXR format. The OpenEXR format has two numerical representations (the normalized number and the denormalized number) which are not in other HDR formats such as RGBE. These two numerical representations cause a problem in applying an integer TMO. The proposed method enables us to avoid the problem by using the intermediate format. Moreover, the exponent part and the mantissa part are processed separately as two integer numbers. As a result, an integer TMO with less numerical range is achieved by our method. The experimental results show that the proposed method can generate high-quality low dynamic range (LDR) images with less memory space.

Tone mapping operators (TMO) are functions that map high dynamic range (HDR) images to a standard dynamic range (SDR), while aiming to preserve the perceptual cues of a scene that govern its visual quality. Despite the increasing number of studies on quality assessment of tone mapped images, current subjective quality datasets have relatively small numbers of images and subjective opinions. Moreover, existing challenges in transferring laboratory experiments to crowdsourcing platforms put a barrier for collecting large-scale datasets through crowdsourcing. In this work, we address these challenges and propose the RealVision-TMO (RV-TMO), a large-scale tone mapped image quality dataset. RV-TMO contains 250 unique HDR images, their tone mapped versions obtained using four TMOs and pairwise comparison results from seventy unique observers for each pair. To the best of our knowledge, this is the largest dataset available in the literature for quality evaluation of TMOs by the number of tone mapped images and number of annotations. Furthermore, we provide a content selection strategy to identify interesting and challenging HDR images. We also propose a novel methodology for observer screening in pairwise experiments. Our work does not only provide annotated data to benchmark existing objective quality metrics, but also paves the path to building new metrics for tone mapping quality evaluation.

In this paper, we propose a tone mapping (TM) method using color correction function (CCF) and image decomposition in high dynamic range (HDR) imaging. The CCF in the proposed TM is derived from the luminance compression function with the color constraint under which the color ratios, between the three color channels of the radiance map and dynamic range compression term, are preserved and color saturation is controlled. The proposed CCF is developed to locally perform the luminance compression and color saturation control in local TM. For image decomposition, we use a bilateral filter and apply the adaptive weight to the base layer of the luminance. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality as well the local contrast. It can be used for contrast and color enhancement in various display and acquisition devices.