基于熵编码的立体视频加密与信息隐藏算法

针对立体视频的安全性,该文提出一种基于熵编码的立体视频加密与信息隐藏算法。首先,结合立体视频编码结构,分析误差漂移的物理机制,并根据立体视觉掩蔽效应,确定左右视点的加密帧和隐秘信息待嵌入帧。其次,在基于上下文自适应二进制算术编码(CABAC)的熵编码中,通过等长码字替换技术,实现立体视频的加密和信息隐藏。实验结果表明,视频码流经加密与信息隐藏之后格式兼容、比特率不变,视频感知质量无明显下降,在计算复杂度和码率增加率上有显著优势。

高动态范围图像融合过程中的噪声抑制算法

高动态范围成像通常需要利用多个不同曝光时间的低动态范围图像来合成高动态范围图像。在合成后图像噪声会进一步放大,可能导致最终的高动态范围图像视觉质量严重降低。针对合成图像需要保留低曝光图像中高亮区域的细节信息以及高曝光图像中低暗区域的细节信息,且图像噪声与亮度有关这一问题,本文提出一种基于亮度分区、噪声水平估计的高动态范围图像融合过程中的噪声抑制算法。首先,根据图像的亮度信息,确定低动态范围图像的不同亮度区域;然后对图像不同亮度区域,利用重叠块估计噪声水平,根据得到的噪声水平,指导图像的稀疏去噪;最后,对处理后的低动态范围图像,采用融合方法合成高动态范围图像。实验结果表明,所提出的算法能有效地抑制图像噪声,合成的高动态范围图像具有更好的视觉质量。

基于张量域感知特征的无参考高动态范围图像质量评价

针对传统的无参考图像质量评价方法不能直接用于高动态范围(HDR)图像的质量评价问题,提出一种基于张量域感知特征的无参考HDR图像质量评价方法.首先通过张量分解得到同时含有亮度失真和色度失真的张量子带图;然后采用自回归(AR)模型来模拟人脑对张量子带图的感知预测,得到张量子带图的感知预测图像;最后采用AR系数表征HDR图像的张量域感知预测特征,结合张量子带图及其感知预测图的动态范围、亮区域占比的特征,使用支持向量回归模型进行回归映射得到图像的客观质量评价分数.在Nantes和EFPL这2个公开的HDR图像库上的实验结果表明,该方法与主观感知具有很好的一致性,评价指标SROCC和PLCC的值均超过0.93, RMSE分别为0.3047和0.3771.

基于极限学习机的全参考立体图像质量评价

立体图像质量评价是评价立体视频系统性能的有效途径,而模拟人类大脑神经网络进行特征提取是立体图像质量评价的关键.为此,提出一种基于极限学习机的全参考立体图像质量评价方法,包括3个阶段:1)对原始和失真立体图像分别进行特征描述,以左图像,右图像和独眼图作为输入信息,采用包含3个隐层的极限学习机将图像信息映射到特征空间,从而得到原始和失真立体图像的特征描述;2)对原始和失真立体图像的特征描述进行相似性度量,从而得到原始和失真立体图像的质量特征;3)采用极限学习机建立得到的12维质量特征与主观评价值的回归模型,并将训练得到的回归模型用于测试阶段,预测得到相应的客观质量评价值.实验结果表明,文中方法在对称和非对称立体图像数据库都取得了较好的性能,与人类的主观感知保持良好的一致性.

基于左右视点相关性的立体图像鲁棒水印方法

针对立体图像版权保护问题,提出了一种基于左右视点相关性的立体图像鲁棒水印方法。由于张量分解能够较好保存图像的主要能量,因此,首先利用彩色视点中RGB三通道之间的相关性,对左右视点分别进行张量分解。每一个视点分解出三个特征图,其中每个视点的第一特征图保留了每个视点中较强的三通道关系。其次,结合左右视点之间的相关性,联合左右视点的第一特征图进行张量分解,得到立体图像的主要能量特征图。最后,将主要能量特征图进行奇异值分解,并嵌入水印从而提高鲁棒性。实验结果表明,该方法具有较高的鲁棒性和不可见性,并且实现了水印的盲提取。

基于随机森林的HEVC复杂度控制方法

高效视频编码(high efficiency video coding,HEVC)具有较高的计算复杂度,而快速编码算法不能在给定编码时间下完成视频编码,因此提出了一种基于随机森林的HEVC复杂度控制方法。首先训练得到3种不同预测准确率的随机森林分类器,实现编码树单元(coding tree unit,CTU)的多种编码配置;然后,通过建立平均深度—复杂度模型为CTU分配复杂度;最后通过平坦度、平均深度、比特和CTU级累计编码误差确定的CTU编码配置完成复杂度控制。实验结果表明,本文算法复杂度控制精度较高,在率失真性能方面优于当前复杂度控制方法。

2-D IMAGE-BASED VOLUMETRIC MODELING FOR PARTICLE OF RANDOM SHAPE

In this paper, an approach to predicting randomly-shaped particle volume based on its two-Dimensional (2-D) digital image is explored. Conversion of gray-scale image of the particles to its binary coun-terpart is first performed using backlighting technique. The silhouette of particle is thus obtained, and conse-quently, informative features such as particle area, centroid and shape-related descriptors are collected. Several dimensionless parameters are defined, and used as regressor variables in a multiple linear regression model to predict particle volume. Regressor coefficients are found by fitting to a randomly selected sample of 501 parti-cles ranging in size from 4.75mm to 25mm. The model testing experiment is conducted against a different ag-gregate sample of the similar statistical properties, the errors of the model-predicted volume of the batch is within ±2%.

SADDLE-POINT BASED SEPARATION OF TOUCHED OBJECTS IN 2-D IMAGE

In many image analysis and processing problems, discriminating the size and shape of each individual object in an aggregate pile projected in an image is an important practice. It is relatively easy to distinguish these features among the objects already separated from each other. The problems will be undoubtedly more complex and of greater challenge if the objects are touched or/and overlapped. This letter presents an algorithm that can be used to separate the touches and overlaps existing in the objects within a 2-D image. The approach is first to convert the gray-scale image to its corresponding binary one and then to the 3-D topographic one using the erosion operations. A template (or mask) is engineered to search the topographic surface for the saddle point, from which the segmenting orientation is determined followed by the desired separating operation. The algorithm is tested on a real image and the running result is adequately satisfying and encouraging.

NEW VISUAL PERCEPTUAL POOLING STRATEGY FOR IMAGE QUALITY ASSESSMENT

Most of Image Quality Assessment (IQA) metrics consist of two processes. In the first process, quality map of image is measured locally. In the second process, the last quality score is converted from the quality map by using the pooling strategy. The first process had been made effective and significant progresses, while the second process was always done in simple ways. In the second process of the pooling strategy, the optimal perceptual pooling weights should be determined and computed according to Human Visual System (HVS). Thus, a reliable spatial pooling mathematical model based on HVS is an important issue worthy of study. In this paper, a new Visual Perceptual Pooling Strategy (VPPS) for IQA is presented based on contrast sensitivity and luminance sensitivity of HVS. Experimental results with the LIVE database show that the visual perceptual weights, obtained by the proposed pooling strategy, can effectively and significantly improve the performances of the IQA metrics with Mean Structural SIMilarity (MSSIM) or Phase Quantization Code (PQC). It is confirmed that the proposed VPPS demonstrates promising results for improving the performances of existing IQA metrics.

Multi-view video color correction using dynamic programming

Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.

A MICRO-IMAGE FUSION ALGORITHM BASED ON REGION GROWING

Due to the limitation of Depth Of Field (DOF) of microscope, the regions which are not within the DOF will be blurring after imaging. Thus for micro-image fusion, the most important step is to identify the blurring regions within each micro-image, so as to remove their undesirable impacts on the fused image. In this paper, a fusion algorithm based on a novel region growing method is proposed for micro-image fusion. The local sharpness of micro-image is judged block by block, then blocks whose sharpness is lower than an adaptive threshold are used as seeds, and the sharpness of neighbors of each seed are evaluated again during the region growing until the blurring regions are identified completely. With the decreasing in block size, the obtained region segmentation becomes more and more accurate. Finally, the micro-images are fused with pixel-wise fusion rules. The experimental results show that the proposed algorithm benefits from the novel region segmentation and it is able to obtain fused micro-image with higher sharpness compared with some popular image fusion method.

Semi-reference image quality metric for virtual view images in free-viewpoint television

A semi-reference image quality assessment metric based on similarity measurement for synthesizedvirtual viewpoint image (WI) in free-viewpoint television system (FTV) is proposed in this paper. Thekey point of the proposed metric is taking resemblant information between WI and its neighbor view imagesfor quality assessment to make our metric to be extended to multi-semi-reference image quality assessmenteasily. The proposed metric first extracts impact factors from image features, then combines animage synthesis technique and similarity functions, in which, disparity information are taken into accountfor registering the resemblant regions. Experiments are divided into three phases. Phase Ⅰ is to verify thevalidation of the proposed metric by taking impaired images and original reference into account. The experimentalresults show the agreement between evaluation scores and bio-characteristic of human visualsystem. Phase Ⅱ shows the accordance with Phase Ⅰ by taking neighbor view as reference. The proposedmetric can be taken as a full reference one to evaluate the image quality even though the original referenceis absent. Phase Ⅲ is then performed to evaluate the quality of ⅤⅥ. Evaluation scores in the experimentalresults are able to evaluate the quality of ⅤⅥ.

A NEW OBJECTIVE STEREOSCOPIC IMAGE ASSESSMENT MODEL BASED ON STEREOSCOPIC PERCEPTION

In order to establish a stereoscopic image quality assessment method which is consistent with human visual perception,we propose an objective stereoscopic image quality assessment method.It takes into account the strong correlation and high degree of structural between pixels of image.This method contains two models.One is the quality synthetic assessment of left-right view images,which is based on human visual characteristics,we use the Singular Value Decomposition(SVD)that can represent the degree of the distortion,and combine the qualities of left and right images by the characteristics of binocular superposition.The other model is stereoscopic perception quality assessment,due to strong stability of image’s singular value characteristics,we calculate the distance of the singular values and structural characteristic similarity of the absolute difference maps,and utilize the statistical value of the global error to evaluate stereoscopic perception.Finally,we combine two models to describe the stereoscopic image quality.Experimental results show that the correlation coefficients of the proposed assessment method and the human subjective perception are above 0.93,and the mean square errors are all less than 6.2,under JPEG,JP2K compression,Gaussian blurring,Gaussian white noise,H.264 coding distortion,and hybrid cross distortion.It indicates that the proposed stereoscopic objective method is consistent with human visual properties and also of availability.

MULTI-EPIPOLAR LINES MATCHING-BASED RAY-SPACE INTERPOLATION FOR FREE VIEWPOINT VIDEO SYSTEM

Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation and compression are two key techniques for the solution. In this paper,correlation among multiple epipolar lines in ray-space data is analyzed,and a new method of ray-space interpolation with multi-epipolar lines matching is proposed. Comparing with the pixel-based matching interpolation method and the block-based matching interpolation method,the proposed method can achieve higher Peak Signal to Noise Ratio(PSNR) in interpolating rayspace data and rendering arbitrary viewpoint images.

CODING-ORIENTED MULTI-VIEW VIDEO COLOR CORRECTION

Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Ggroup Oof Ppictures (GOP) by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results show the proposed method can obtain better perform-ances in color correction and multi-view video coding.

Dynamic programming based ray-space interpolation for free-viewpoint video system

This paper presents a free viewpoint video(FVV)system based on ray-space interpolation method.The new algorithm matches individual pixels in corresponding scanline pairs by using a dynamic program-ming technique.A sparse intermediate view disparity map is projected from matched pixels firstly,andthe holes(occluded pixels)are filled in by propagating the disparity of neighboring background pixels.After interpolating dense view images,an arbitrary virtual view image can be easily rendered from thedense ray-space converted from these view images.The proposed method is evaluated on the Middleburydata set arid compared with other methods,experimental results show that the better quality of the inter-mediate view is obtained and the corresponding computational complexity is reduced significantly.

融合结构与非结构信息的自然图像恰可察觉失真阈值估计

目的研究表明,图像的恰可察觉失真(JND)阈值主要与视觉系统的亮度适应性、对比度掩模、模块掩模以及图像结构等因素有关。为了更好地研究图像结构对JND阈值的影响,提出一种基于稀疏表示的结构信息和非结构信息分离模型,并应用于自然图像的JND阈值估计,使JND阈值模型与人眼视觉系统具有更好的一致性。方法首先通过K-均值奇异值分解算法(K-SVD)得到过完备视觉字典。然后利用该过完备字典对输入的自然图像进行稀疏表示和重建,得到该图像对应的结构层和非结构层。针对结构层和非结构层,进一步设计基于亮度适应性与对比度掩模的结构层JND估计模型和基于亮度对比度与信息不确定度的非结构层JND估计模型。最后利用一个能够刻画掩模效应的非线性可加模型对以上两个分量的JND估计模型进行融合。结果本文提出的JND估计模型利用稀疏表示将自然图像的结构/非结构信息进行分离,然后采用符合各自分量特点的JND模型进行计算,与视觉感知机理高度一致。实验结果表明,本文JND模型能够有效地预测自然图像的JND阈值,受污染图的峰值信噪比(PSNR)值比其他3个JND对比模型值高出3 5 d B。结论与现有模型相比,该模型与人眼主观视觉感知具有更好的一致性,更能有效地预测自然图像的JND阈值。