基于图像特征的色调映射方法评价体系

为解决高动态范围图像在传统显示设备中准确显示的问题,将模糊的视觉注意机制转化为确定的特征点个数,提出一种基于图像特征的评价体系,以判别色调映射方法所得结果图像是否保持特征信息。针对图像进行对比度调整,将场景亮度变换到可以显示的范围,同时保持细节与颜色等对于表现原始场景的重要信息。对7种色调映射全局方法,即Logarithmic TMO,Exponential TMO,TumblinRushmeier TMO,Schlick TMO,Ferwerda TMO,Ward Hist Adj TM O,Drago TM O进行比较分析,得出Ward Hist Adj TM O色调映射的整体效果最优。     

基于交叉皮质模型的高动态范围图像可视化方法

针对高动态范围图像(HDRI)在低动态范围显示设备上的可视化问题,提出基于交叉皮质模型(ICM)的色调映射算法,其在融入人类视觉特性的同时兼顾了全局亮度和局部细节保持.首先将线性热流(LHF)应用于向心自动波(CA)的实现,构成LHF-CA-ICM,以解决原有ICM自动波效应的负面影响;然后根据LFH-CA-ICM迭代...     

交会对接仿真电视图像TMO算法主观评价

通过对实时渲染仿真交会对接电视图像的主观评价,指出调和映射处理(TMO)算法的修正是提高仿真场景逼真度的方法.基于交会对接仿真电视图像TMO算法应用,分别针对S-curve算法、自适应对数算法和Reinhard算法设计了基于静态图像对比的亮度调和因子评价实验和基于动态场景对比的算法应用距离段评价实验,并对实验结果的均值、标准差以及HSD值进行了计算与分析;上述3种算法亮度调和因子分别为6.0,0.6和2.2,依次应用于远距离,中、近距离和靠拢距离时仿真电视图像有最佳评价和显示效果.实验结果表明,采用同种TMO算法处理的交会对接仿真图像动态场景真实感效果优于静态图像;在交会对接不同距离段内,仿真场景需要采用不同的TMO渲染方法.     

高动态范围图像的生成与显示方法研究

高动态范围图像的高动态性使得高动态范围图片在现有数码设备上捕获相当困难,同时基于现有显示及打印设备的低动态特性高动态范围图片的显示也十分棘手,本文将介绍并分析近年来有关高动态范围图像的生成及显示方法,比较其优劣,并对典型方法进行详细论述。     

数字摄像机的高动态范围曝光算法及实现

在机器视觉领域,许多应用对摄像机的动态范围提出了苛刻的要求.对数曲线响应传感器的出现为图像动态范围的提升奠定了硬件基础.然而目前针对该传感器的曝光控制均需人工操作评估,自动性、实时性差.为了解决这个问题,提出了一种基于对数曲线响应传感器的高动态范围自动曝光算法,并基于现场可编程门阵列(FPGA)并行计算在硬件上实现该算...     

高动态图像色调映射技术新进展*

传统显示设备受自身动态范围限制,无法很好地显示高动态图像的效果,需要用色调映射方法进行合理的动态域压缩,获得更好的图像显示质量。综述了现有高动态图像的色调映射技术,首先简要介绍了高动态图像色调映射方法的概念;再介绍了色调映射算子的分类,以色调映射处理方式为主分别介绍了空域不变算法、空域变化算法及混合算法这三大类算子近年来发展起来的各种新方法,并指出各种方法的技术优势及对此进行了归纳总结;最后阐述了该技术的应用领域及其继续发展的方向。     

基于相机阵列的高动态范围图像合成方法

针对传统的高动态范围图像合成方法不能适应动态光照的问题, 提出了基于相机阵列的不同曝光的多幅图像的配准及高动态范围图像合成方法。首先利用相机阵列获取不同曝光图像, 结合相机阵列标定参数, 采用光场合成孔径理论对图像进行配准, 并对配准后的图像作中值位图进行二次配准。根据拟合出的各相机的光照响应曲线, 进而将二次配准后的不同曝光的图像合成为一幅高动态范围图像。实验表明, 该方法可以有效地在动态光照下合成高动态范围图像, 取得了不错的效果。     

亮度分区自适应对数色调映射算法*

色调映射可将高动态范围图像显示在低动态范围显示器上。常用的对数全局色调映射算法由于压缩范围有限容易引起细节丢失,为此本文给出一种基于亮度分区的自适应对数色调映射算法。首先将高动态范围图像由RGB颜色空间转换为XYZ颜色空间以提取图像亮度信息,然后将亮度图分为高、中、低三个照度区域。根据区域亮度属性实施对数色调映射实现动态范围局部压缩,并进行融合处理以消除区域交界处的显示效果。同时采用双边滤波技术进行细节补偿。实验结果表明,此算法能有效压缩动态范围并再现真实场景信息,同时可以保留丰富的细节。     

高动态范围成像技术中的鬼影检测与去除方法综述

由于广泛的实用价值与理论价值,高动态范围成像(HDRI)技术成为图像处理领域的一个研究热点,如何检测及去除成像过程中产生的干扰影像(即“鬼影”)也引起了研究者的广泛关注。将鬼影检测与去除方法按照运动物体是否属于拍摄目标及算法操作域进行系统分类,将鬼影检测算法分为无参考图像、有参考图像两大类并将每一大类分为辐射域检测、图像域检测两类,将鬼影去除算法分为辐射域去除、图像域去除两大类,对其中每一类算法分别全面综述了其特点及最新研究成果,并对不同方法的优缺点进行了比较分析。最后总结了不同方法的适用条件并给出了关于这一课题未来发展的思考。     

源于现实，超越现实说说HDR摄影

HDRI,高动态范围影像,通常被简化为HDR。对场景按不同曝光值进行多次曝光,捕捉到该场景的所有动态范围,再通过HDR软件进行处理,便得到一幅相似于人眼所见的该场景其高光和阴影部分的细节一览无余。     

A framework for inverse tone mapping

In recent years many tone mapping operators (TMOs) have been presented in order to display high dynamic range images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The inverse of tone mapping, inverse tone mapping, expands a low dynamic range image (LDRI) into an HDRI. HDRIs contain a broader range of physical values that can be perceived by the human visual system. We propose a new framework that approximates a solution to this problem. Our framework uses importance sampling of light sources to find the areas considered to be of high luminance and subsequently applies density estimation to generate an expand map in order to extend the range in the high luminance areas using an inverse tone mapping operator. The majority of today’s media is stored in the low dynamic range. Inverse tone mapping operators (iTMOs) could thus potentially revive all of this content for use in high dynamic range display and image based lighting (IBL). Moreover, we show another application that benefits quick capture of HDRIs for use in IBL.     

基于图像的光照

基于图像的光照技术是利用现实世界的光照图像来照明现实的或计算机生成的场景及物体的一种方法。介绍了基于图像光照的基本方法和步骤，在LightWave 3D图形软件中建立三维物体模型，加入高动态范围图像作为场景照明环境，通过光通量与高动态范围图像的结合，获得了逼真的光照及环境映射图像。     

不同曝光值图像的直接融合方法

提出了一种直接从同一场景多次不同曝光值下成像的LDR(low dynamic range)图像序列中提取每个像素位置最佳成像信息的图像融合方法,可以在无需任何拍摄相机参数及场景先验信息的情况下,快速合成适合在常规设备上显示的HDR(high dynamic range)图像.该方法利用特殊设计的鲁棒性曲线拟合算法建立LDR图像序列中每个像素位置像素值曲线的数学模型,并由此给出评价单个像素成像时曝光合适程度的标准和融合最佳成像像素信息的方法.对不同场景的大量实验结果显示,该方法的计算结果与传统HDR成像技术经过复杂的HDR重建和色调映射计算后得到的结果相当,但具有更高的计算效率,并同时对图像噪声、相机微小移动和运动目标的影响具有较好的鲁棒性.     

高动态范围图像梯度压缩算法

高动态范围（HDR）图像是一种可以表示实际场景中亮度大范围变化的图像类型,图像中的像素值正比于场景中对应点的实际亮度值,因此,可以更好地表示场景中亮区和暗区的光学特性。为了在常规显示硬件上显示HDR图像,采用梯度压缩算法,在亮度图像梯度域上对大梯度进行衰减,压缩图像亮度的动态范围。实验结果表明,该算法能对HDR图像进行较高视觉质量的显示。     

HDR image compression and evaluation based on local adaptation using a retinal model

Abstract— The retinal adaptation process helps the human visual system to see high‐dynamic‐range (HDR) scenes in the real world. A simple static local adaptation method for HDR image compression based on a retinal model is presented. The proposed simple model aims at recreating the same sensations of the human visual system between the real‐world scene and the range compressed image on the display device when viewed after the human visual system reaches the steady local adaptation state, respectively. In computing scene local adaptation, the use of a non‐linear edge‐preserving bilateral filter not only presents a better tonal rendition in compressing local contrast and preserving details but also avoids banding artifacts across high‐gradient edges. Our new model relates the display adaptation with the scene adaptation based on the retinal model. In order to verify the effectiveness, a subjective evaluation is made by comparing the real scene and the display image using the paired comparison technique.     

Convolutional Sparse Coding for High Dynamic Range Imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially‐varying pixel exposures. In this paper, we propose a novel algorithm to recover high‐quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently‐introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher‐quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform.     

Motion Aware Exposure Bracketing for HDR Video

Mobile phones and tablets are rapidly gaining significance as omnipresent image and video capture devices. In this context we present an algorithm that allows such devices to capture high dynamic range (HDR) video. The design of the algorithm was informed by a perceptual study that assesses the relative importance of motion and dynamic range. We found that ghosting artefacts are more visually disturbing than a reduction in dynamic range, even if a comparable number of pixels is affected by each. We incorporated these findings into a real‐time, adaptive metering algorithm that seamlessly adjusts its settings to take exposures that will lead to minimal visual artefacts after recombination into an HDR sequence. It is uniquely suitable for real‐time selection of exposure settings. Finally, we present an off‐line HDR reconstruction algorithm that is matched to the adaptive nature of our real‐time metering approach.     

Evaluation of HDR tone‐mapping algorithms using a high‐dynamic‐range display to emulate real scenes

Abstract— Current HDR display technology approaches the dynamic‐range capabilities of the fully adapted human visual system. As such, this technology has potential for performing as a surrogate for real‐world scenes in the perceptual evaluation of high‐dynamic‐range (HDR) image‐reproduction algorithms that aim to map HDR scenes to the limited dynamic ranges available in typical display and print technology. Compared with direct image assessment in comparison with real‐world scenes, it is clear that use of HDR display technology has the benefit of simplicity in experimental design while maintaining the HDR of the original scene. To evaluate this potential application of HDR display technology, seven published versions of well‐known HDR tone‐mapping algorithms were benchmarked for perceptual rendering accuracy against each of four real‐world scenes constructed in the laboratory and against corresponding images on an HDR display. The results illustrate that visual assessments obtained from the HDR display and those obtained from real‐world scenes are in good agreement, validating the potential for HDR display technology as an evaluation tool in this context.     

Evaluation of tone mapping operators in night-time virtual worlds

The subjective quality of a virtual world depends on the quality of displayed images. In the present paper, we address a technical aspect of image quality in virtual environments. Due to the recent development of high dynamic range (HDR) imaging in computer graphics applications, tone mapping operators (TMO) are needed in the graphic pipeline, and their impact on the final image quality needs to be tested. Previous evaluations of such operators have emphasized the fact that the specific merit of a given operator may depend on both the scene and the application. The dynamic behavior of tone mapping operators was not tested before, and we have designed two psychophysical experiments in order to assess the relevance of various TMO for a specific class of virtual worlds, outdoor scenes at night and an interactive application, to explore an outdoor virtual world at night. In a first experiment, 5 HDR video clips were tone-mapped using 8 operators from the literature, resulting in 40 videos. These 40 videos were presented to 14 subjects, which were asked to rate their realism. However, the subject’s evaluation was not a direct comparison with the HDR videos. In a second experiment, 9 HDR photographs of urban scenes at night were tone-mapped with the same 8 operators. The resulting 72 photographs were presented to 13 subjects, at the location where the photographs were taken. The subjects were asked to rate the realism of each tone-mapped image, displayed on a laptop, with respect to the physical scene they experienced. The first experiment emphasized the importance of modeling the temporal visual adaptation for a night-time application.