松下在广播电视HDR应用的探讨

1.HDR标准 主流的HDR标准有两个.一个是ST2084,也就是常说的PQ方式.由杜比提案,现在已经被一些支持HDR的播放器所支持.在PQ方式下,电视机显示亮度从100尼特提高到10000尼特.这种HDR方式最终在监视器显示的时候,是根据绝对亮度值进行编码,例如0.01尼特用64进行编码,10000尼特用1019进行编码.对于电视机的衔接器件而言,最多能达到1000到2000尼特的亮度值,所以PQ很多没有利用下来.     

一种基于LCD-LED双调制显示器的HDR图像显示方法

提出一种针对HDR图像的显示方法,该方法应用于LCD-LED双调制高动态显示器,旨在使显示器更好地显示HDR图像要求的亮度细节,提高视觉质量。首先,建立HDR图像亮度与LED亮度范围对应关系,使用光扩散函数作为背光LED亮度取值范围的权重。然后,统计LED的亮度辐射区域内不同LED发光强度等级的权重,取权重最大者对应的亮度作为该背光LED亮度。最后,利用依据LED亮度生成LED背光扩散图像与HDR图像计算出LCD显示图像。仿真结果表明,该算法可以使显示器亮度失真率系数低至0.006以下。在LCD-LED双调制高动态显示器上实验验证结果表明,该算法可以有效提高图像的层次感,有效抑制LCD-LED双调制高动态显示器的"光晕"以及亮度截断现象,提高显示质量。     

一种亮度分区和导向滤波相结合的色调映射算法

针对高动态范围(High Dynamic Range,HDR)图像的动态范围与普通显示设备不匹配的问题,本文提出了一种亮度分区和导向滤波相结合的色调映射算法。首先,通过颜色空间转换将输入的HDR图像转换到CIEL*a*b*空间,得到亮度层和色度层图像,接着对亮度层图像进行对数压缩并分区,对压缩后的各分区亮度图像选取合适γ值进行校正。然后,对于现有映射算法过于强调对图像亮度的处理而忽略色度的问题,本文将压缩后的亮度图像作为引导图像对色度层图像进行导向滤波处理。最后,将处理后的亮度层图像和色度层图像融合得到标准动态范围(Standard Dynamic Range,SDR)图像。通过对比实验表明,本文算法得到的图像在清晰度、信息熵、方差方面较全局映射法、局部映射法和双边滤波法平均提高了94.03%、30.73%和24.23%,说明本文算法在实现高动态图像亮度压缩的同时,更好地实现了对色度和局部细节的处理。     

基于双边滤波的多尺度分层色调映射算法

为增强高动态范围图像(High dynamic range,HDR)的显示效果,本文提出一种多尺度梯度域色调映射算法。首先提取高动态范围图像的亮度信息,利用双边滤波将高动态范围图像的亮度数据进行多尺度分解,得到基本层和细节层。由于视觉上的亮度变化体现为图像数据的梯度变化,因此可在梯度域对基本层图像进行自适应动态范围压缩,然后加上细节层图像信息,最后再通过色彩校正算法恢复图像色彩,实现HDR图像的动态范围压缩。通过对比算法的定量分析表明,本文算法的方差和信息熵的客观指标分别提高了30.8%和5.9%,因此,本文方法在压缩HDR图像的动态范围的同时,可以更好地保留边界、纹理等细节信息。     

基于对比敏感度函数的高动态范围视频编码

考虑到HDR视频高动态范围和高精度的特殊性以及人眼视觉感知的复杂性,提出一种基于 对比敏感度函数的高动态范围(HDR)视频编码率失真优化算法。首先,根据对比敏感度函数( CSF)的定义得出对比敏感度(CS)与人眼对误差敏感 程度的关系;然后,针对10比特HDR视频的亮度分量,以树形编码单 元(CTU,coding tree un it)为基本单位,求取影响视觉对比敏感度的适应亮度值以及空间频率的大小;最后,进 一步修正对比敏感度值作为视觉感知因子,对HEVC编码过程中每个CTU的拉格朗日因子 进行缩放,实现更加符合视觉感知的码率分配,去除感知冗余。实验结果显示,在相同 HDR-VDP-2.2的Q因子和PSNR_DE分值下,和原始编码平台相比 ,码率平均节省5.6%和8.3%,有效提升HDR视频编码压缩的性能。     

采用联合特征的H.266/VVC屏幕内容快速模式选择算法

新一代视频编码标准H.266/VCC针对屏幕内容编码引入帧内块复制、调色板等预测模式,在提高编码效率的同时也带来了巨大的计算复杂度。本文采用角点、水平/垂直活动度和平均颜色亮度差联合特征对屏幕内容视频帧和当前编码单元（Coding Unit, CU）进行分类,将视频帧分为低对比度屏幕视频帧和高对比度屏幕视频帧,将CU细分为自然内容背景CU、屏幕内容背景CU和屏幕内容前景CU,进而对CU模式进行选择性跳过,减少模式选择代价。实验结果显示,在全帧内的条件下,该算法与开启IBC和PLT的H.266/VVC VTM-7.3标准相比,在码率仅增加1.21%的情况下节省了26.41%的编码时间,降低了编码复杂度。      

基于主成分分析和引导滤波的色调映射算法

针对传统高动态范围(HDR)图像色调映射算法普遍 存在色偏和效率低的问题,提出了一种基于主成分 分析(PCA)进行色彩空间转换和具有边缘保持特性的引导滤波图像增强的色调映射算法。首 先利用图像的平均亮 度实现图像Gamma自适应校正;然后采用PCA方法将图像的3个颜色分量转换为相 互正交的亮度 分量和色差分量,模拟相机响应函数(CRF)曲线压缩亮度分量的动态范围,并将结果与加权 后的色差分量联合, 经PCA逆转换得到新的RGB分量;最后利用引导滤波方法对图像进行增强,提高 图像对比度,避 免光晕现象。实验结果表明,本文算法效率比经典的iCAM06算法提高了4倍以 上,并能有效避免偏色和 光晕现象,处理后图像的细节清晰层次感强、色彩自然丰富,不仅能用于传统的便携式显示 设备,而且可用于穿戴式智能视觉辅助设备和无屏幕显示器等新兴领域。     

基于S曲线全局动态调光的改进算法

S曲线全局动态调光算法可以降低LED液晶显示器的功耗,同时能够提高显示图像的静态对比度,但该算法会造成部分图像色彩失真和细节丢失。针对这一问题,本文提出一种图像细节层分离与视觉显著性理论相结合的S曲线改进算法。首先,将原始图像转换至HSV色彩空间进行亮度和色度分离;然后,在图像亮度分量上采用双边滤波得到图像的基础层与细节层,基础层采用S曲线进行动态范围拉伸,实现像素补偿,细节层则运用视觉显著性理论进行分区与权值增强,弥补由像素补偿带来的细节损失;最后,将处理后的各层图像转换至RGB空间显示。将本文算法的仿真结果与原S曲线算法的结果进行对比。结果显示,本文算法在维持原算法功耗降低和静态对比度提升水平不变的基础上,解决了原算法在部分图像中出现的色彩失真和细节丢失问题,提升了图像的视觉显示效果,同时本文算法的仿真结果具有更大的信息熵和平均梯度。     

基于人眼亮度阈值特性的图像增强算法

结合人眼视觉特性,提出一种面向人眼视觉的图像增强算法。在保持原图像所有像素灰度大小关系不发生倒序的前提下,以人眼可分辨的像素对数作为目标函数。为使目标函数实现最大化,首先根据人眼亮度阈值特性测试指定显示器的人眼最多可分辨的灰度级数;然后结合图像本身的灰度级数与人眼最多可分辨的灰度级数使用一种动态规划灰度级合并算法,使得灰度合并后图像中包含的灰度级数不多于人眼最多可分辨灰度级数;最后对合并后的灰度按人眼视觉亮度阈值特性做一一映射。本文算法充分考虑了图像观测过程中人眼感知与显示器显示亮度,具有明确的目标函数,图像增强效果优于目前常用算法。     

高动态范围图像色调映射算法研究

高动态范围(High Dynamic Range,HDR)图像依托自身场景性能的优越性,近年来备受瞩目.然而,HDR图像显示设备由于成本和技术问题而难以普及,HDR图像必须经过色调映射(Tone-Mapping,TM)才能由传统显示器生成自适应低动态范围(Low Dynamic Range,LDR)的数据.近年来,TM技术发展迅猛,但也衍生出一系列问题.对此,首先通过HDR图像TM算法,在算法上将其分化为整体色调映射算法、部分色调映射算法以及混合色调映射算法;其次分析其优缺点,并对一些经典方法进行实验分析,比较算法的性能;最后总结TM技术的发展趋势.     

Comparing Signal Detection Between Novel High-Luminance HDR and Standard Medical LCD Displays

DICOM specifies that digital data values should be linearly mapped to just-noticable differences (JNDs) in luminance. Increasing the number of JNDs available requires increasing the display's dynamic range. However, operating over too wide a range may cause human observers to miss contrast in dark regions due to adaptation to bright areas or, alternatively, miss edges in bright regions due to scattering in the eye. Dolby Inc.'s high dynamic range (HDR) LCD display has a maximum luminance over 2000 $ {hbox{cd/m}}^{2}$; bright enough to produce significant in-eye scatter. The display combines a spatially variable backlight producing a low-resolution 8-bit “backlight image” with a high-resolution 8-bit LCD panel, approximating a 16-bit greyscale display. Alternatively, by holding the backlight constant at 800 $ {hbox{cd/m}}^{2}$, a standard medical LCD display can be simulated.      

HDR-VQM: An objective quality measure for high dynamic range video

High dynamic range (HDR) signals fundamentally differ from the traditional low dynamic range (LDR) ones in that pixels are related (proportional) to the physical luminance in the scene (i.e. scene-referred). For that reason, the existing LDR video quality measurement methods may not be directly used for assessing quality in HDR videos. To address that, we present an objective HDR video quality measure (HDR-VQM) based on signal pre-processing, transformation, and subsequent frequency based decomposition. Video quality is then computed based on a spatio-temporal analysis that relates to human eye fixation behavior during video viewing. Consequently, the proposed method does not involve expensive computations related to explicit motion analysis in the HDR video signal, and is therefore computationally tractable. We also verified its prediction performance on a comprehensive, in-house subjective HDR video database with 90 sequences, and it was found to be better than some of the existing methods in terms of correlation with subjective scores (for both across sequence and per sequence cases). A software implementation of the proposed scheme is also made publicly available for free download and use.     

Tone mapping with contrast preservation and lightness correction in high dynamic range imaging

In real-world environments, the human visual system perceives a wide range of luminance in a scene. However, the full range of tones in a high dynamic range (HDR) scene cannot be displayed on standard display devices due to their low dynamic range (LDR). Therefore, tone mapping is necessary to faithfully display a HDR scene on an LDR display device. Existing tone mapping methods have problems because details and contrast in a scene are not preserved faithfully, and they also distort the colors in a scene. Thus, we propose a tone mapping method for preserving the detail in an HDR scene using a weighted least squares filter, which preserves the global contrast in a scene by using a competitive learning neural network, before applying a tone reproduction operator to preserve the color without shifting the lightness. According to the Helmholtz–Kohlrausch effect, the perception of brightness depends on the lightness, chroma, and hue of a color. For example, the luminance of pixels with specific colors such as red and blue is low in an HDR scene. The proposed method corrects the lightness of pixels according to the color (i.e., lightness, chroma, and hue) of a tone-mapped image. Experimental results with several test sets of images demonstrated that the proposed tone mapping method with contrast preservation and lightness correction is more suitable for dynamic range compression than existing tone mapping methods, while it also preserves the color of a scene in an effective way.     

Blind tone mapped image quality assessment with image segmentation and visual perception

With tone mapping, high dynamic range (HDR) image contents can be displayed on low dynamic range (LDR) display devices, in which some important visual information may be distorted. Thus, the tone mapped image (TMI) quality assessment is one of important issues in HDR image/video processing fields. Considering the difference of visual distortion degrees between the flat and complex regions in TMI, and considering that high-quality TMI should preserve as much information as possible of its original HDR image especially in the high/low luminance regions, this paper proposes a new blind TMI quality assessment method with image segmentation and visual perception. First, we design different features to describe the distortion of TMI’s different regions with two kinds of TMI segmentation. Then, considering that there lacks an efficient algorithm to quantify the importance of features, a feature clustering scheme is designed to eliminate the poor effect feature components in the extracted features to improve the effectiveness of the selected features. Finally, considering the diversity of tone mapping operator (TMO), which may cause global and local distortion of TMI, some other global features are also combined. At last, a final feature vector is formed to synthetically describe the distortion in TMI and used to blindly predict the TMI’s quality. Experimental results in the public ESPL-LIVE HDR database show that the Pearson linear correlation coefficient and Spearman rank order correlation coefficient of the proposed method reach 0.8302 and 0.7887, respectively, which is superior to the state-of-the-art blind TMI quality assessment methods, and it means that the proposed method is highly consistent with human visual perception.     

Enabling stereoscopic high dynamic range video

Stereoscopic and high dynamic range (HDR) imaging are two methods that enhance video content by respectively improving depth perception and light representation. A large body of research has looked into each of these technologies independently, but very little work has attempted to combine them due to limitations in capture and display; HDR video capture (for a wide range of exposure values over 20 f-stops) is not yet commercially available and few prototype HDR video cameras exist. In this work we propose techniques which facilitate stereoscopic high dynamic range (SHDR) video capture by using an HDR and LDR camera pair. Three methods are proposed: one based on generating the missing HDR frame by warping the existing one using a disparity map; increasing the range of LDR video using a novel expansion operator; and a hybrid of the two where expansion is used for pixels within the LDR range and warping for the rest. Generated videos were compared to the ground truth SHDR video captured using two HDR video cameras. Results show little overall error and demonstrate that the hybrid method produces the least error of the presented methods.     

Methods for improving the tone mapping for backward compatible high dynamic range image and video coding

Backward compatibility for high dynamic range image and video compression forms one of the essential requirements in the transition phase from low dynamic range (LDR) displays to high dynamic range (HDR) displays. In a recent work [1], the problems of tone mapping and HDR video coding are originally fused together in the same mathematical framework, and an optimized solution for tone mapping is achieved in terms of the mean square error (MSE) of the logarithm of luminance values. In this paper, we improve this pioneer study in three aspects by considering its three shortcomings. First, the proposed method [1] works over the logarithms of luminance values which are not uniform with respect to Human Visual System (HVS) sensitivity. We propose to use the perceptually uniform luminance values as an alternative for the optimization of tone mapping curve. Second, the proposed method [1] does not take the quality of the resulting tone mapped images into account during the formulation in contrary to the main goal of tone mapping research. We include the LDR image quality as a constraint to the optimization problem and develop a generic methodology to compromise the trade-off between HDR and LDR image qualities for coding. Third, the proposed method [1] simply applies a low-pass filter to the generated tone curves for video frames to avoid flickering during the adaptation of the method to the video. We instead include an HVS based flickering constraint to the optimization and derive a methodology to compromise the trade-off between the rate-distortion performance and flickering distortion. The superiority of the proposed methodologies is verified with experiments on HDR images and video sequences.     

OLED平板电视显示性能测量方法与发展趋势研究

OLED电视以其优秀的显示特性得到了专业人士的认可,并在高端市场逐渐推广普及.OLED电视在未来一段时间有极大可能与液晶电视平分秋色.针对OLED平板电视显示性能,结合OLED电视显示原理特点与SJ 11348《数字电视平板显示器测量方法》、SJ/T 11292《计算机用液晶显示器通用规范》设计了对OLED电视的9项显示性能参数的测试方法并对样机进行了测试,此测试方案设计具有合理性与适用性,在实际测量中得到了良好的应用.     

Recovering high dynamic range by Multi-Exposure Retinex

The matter of generating high dynamic range (HDR) image from a number of differently exposed pictures arises to satisfy the needs of high-quality imaging and industrial applications. A number of HDR image generation algorithms have been proposed in the past. However, the HDR radiance map recovered by these classical methods cannot completely exclude the noisy pixels in the input images and thus are unable to produce the optimal result with highest possible SNR. In this paper we are going to introduce a new HDR generation algorithm based on the Multi-Exposure Retinex model deduced in this paper for HDR image composition. The luminance component L and the reflectance R are synthesized independently before being combined together. A novel R image composition method is introduced to help the composed result image reach the highest possible SNR. The method is tested on grey-level images in this paper, but it can be easily extended to the color-image version.