Saliency detection in the compressed domain for adaptive image retargeting

Saliency detection plays important roles in many image processing applications, such as regions of interest extraction and image resizing. Existing saliency detection models are built in the uncompressed domain. Since most images over Internet are typically stored in the compressed domain such as joint photographic experts group (JPEG), we propose a novel saliency detection model in the compressed domain in this paper. The intensity, color, and texture features of the image are extracted from discrete cosine transform (DCT) coefficients in the JPEG bit-stream. Saliency value of each DCT block is obtained based on the Hausdorff distance calculation and feature map fusion. Based on the proposed saliency detection model, we further design an adaptive image retargeting algorithm in the compressed domain. The proposed image retargeting algorithm utilizes multioperator operation comprised of the block-based seam carving and the image scaling to resize images. A new definition of texture homogeneity is given to determine the amount of removal block-based seams. Thanks to the directly derived accurate saliency information from the compressed domain, the proposed image retargeting algorithm effectively preserves the visually important regions for images, efficiently removes the less crucial regions, and therefore significantly outperforms the relevant state-of-the-art algorithms, as demonstrated with the in-depth analysis in the extensive experiments.     

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Video saliency detection incorporating temporal information in compressed domain

Saliency detection is widely used to pick out relevant parts of a scene as visual attention regions for various image/video applications. Since video is increasingly being captured, moved and stored in compressed form, there is a need for detecting video saliency directly in compressed domain. In this study, a compressed video saliency detection algorithm is proposed based on discrete cosine transformation (DCT) coefficients and motion information within a visual window. Firstly, DCT coefficients and motion information are extracted from H.264 video bitstream without full decoding. Due to a high quantization parameter setting in encoder, skip/intra is easily chosen as the best prediction mode, resulting in a large number of blocks with zero motion vector and no residual existing in video bitstream. To address these problems, the motion vectors of skip/intra coded blocks are calculated by interpolating its surroundings. In addition, a visual window is constructed to enhance the contrast of features and to avoid being affected by encoder. Secondly, after spatial and temporal saliency maps being generated by the normalized entropy, a motion importance factor is imposed to refine the temporal saliency map. Finally, a variance-like fusion method is proposed to dynamically combine these maps to yield the final video saliency map. Experimental results show that the proposed approach significantly outperforms other state-of-the-art video saliency detection models.     

基于数据挖掘的图像压缩域肤色检测算法

提出了一种直接在JPEG图像压缩域进行肤色检测的算法。该算法首先在熵解码后的DCT系数中提取图像块的颜色特征和纹理特征,然后利用数据挖掘建立用于表征压缩域图像特征和肤色检测结果之间关系的肤色模型,并利用该模型进行初步肤色检测,最后利用区域生长的方法分割出图像中的肤色区域。实验结果表明,与像素域的SPM (Skin Probability Map)肤色检测算法相比,本文方法可以获得更高的检测准确率和更快的检测速度。     

Moving object segmentation in DCT-based compressed video

A block-based automatic segmentation algorithm has been developed for detecting and tracking moving objects in DCT-based compressed video. The proposed algorithm segments moving objects with block resolution using the stochastic behaviour of the image blocks in the DCT domain     

一种用于帧内篡改检测的压缩感知视频水印实现算法

 针对视频水印在帧内篡改检测方面定位精度的不足,通过压缩感知对MPEG-4(Moving Picture Experts Group-4)视频内容的特征表示,提出一种新的视频水印生成方法及其帧内篡改检测算法.该算法由压缩感知DCT(Discrete Cosine Transform)测量矩阵对I-VOP(Intra-Video Object Plane)图像提取U、V特征参数,生成基于内容的压缩感知视频水印数据并嵌入到图像Y分量的DCT中高频系数中实现帧内篡改检测.实验结果表明,与Hash视频水印算法比较,压缩感知视频水印数据具有更好的恢复能力,且水印算法对视频帧内篡改定位精度更高.     

L/M-fold image resizing in block-DCT domain using symmetric convolution

Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames on digital media are given in a compressed domain. Image resizing of a compressed image can be performed in the spatial domain via decompression and recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in the spatial domain. We propose a novel approach to resize images with L/M resizing ratio in the discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT (multiplication in the spatial domain corresponds to symmetric convolution in the DCT domain). When an image is given in terms of its 8/spl times/8 block-DCT coefficients, its resized image is also obtained in 8/spl times/8 block-DCT coefficients. The proposed approach is computationally fast and produces visually fine images with high PSNR.     

面向检索的压缩域空时视频目标检测与分割

面向语义视频检索,提出一种压缩域的目标分割新算法。它直接基于压缩码流中运动矢量和DCT系数,经过运动检测、矢量分水岭分割、目标融合与修正、后处理与跟踪等步骤提取空时视频目标。整个过程主要基于压缩域进行,无需视频码流的完全解码。对不同测试序列的实验测试结果显示算法能基于压缩域提取较为精确的空时视频目标,并具有较好的鲁棒性。     

基于LDPC码的自适应视频水印算法研究

根据视频水印系统和数字通信系统相似的特性,提出了一种基于LDPC码的自适应视频水印算法。水印信息经随机置换与LDPC编码,对经过二次整数变换之后的直流分量进行修改实现水印的嵌入。为了兼顾水印的不可见性与鲁棒性的要求,算法根据水印长度和变换之后系数的大小自适应地选择嵌入水印的组及系数的改变强度。实验结果表明:该算法能够保证很好的视频质量,较之基于DCT变换的水印算法嵌入速度更快,并实现了水印的盲提取。对于常见的视频攻击有较强的鲁棒性,在码率高于汉明界推导出的下限的情况下,算法鲁棒性随着码率的减小而增强。      

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 88 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform (DCT) is applied to generate DCT coefficients: one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Compressed domain video saliency detection using global and local spatiotemporal features

A compressed domain video saliency detection algorithm, which employs global and local spatiotemporal (GLST) features, is proposed in this work. We first conduct partial decoding of a compressed video bitstream to obtain motion vectors and DCT coefficients, from which GLST features are extracted. More specifically, we extract the spatial features of rarity, compactness, and center prior from DC coefficients by investigating the global color distribution in a frame. We also extract the spatial feature of texture contrast from AC coefficients to identify regions, whose local textures are distinct from those of neighboring regions. Moreover, we use the temporal features of motion intensity and motion contrast to detect visually important motions. Then, we generate spatial and temporal saliency maps, respectively, by linearly combining the spatial features and the temporal features. Finally, we fuse the two saliency maps into a spatiotemporal saliency map adaptively by comparing the robustness of the spatial features with that of the temporal features. Experimental results demonstrate that the proposed algorithm provides excellent saliency detection performance, while requiring low complexity and thus performing the detection in real-time.     

一种用于网络动画过滤的文字提取方法

网络动画中往往包含丰富的字符信息,如果能够将这些字符信息加以提取和识别,将对网络动画的有效过滤具有重要意义。论文介绍了一种新的基于类边缘文本提取算法及其实现,该算法利用DCT方法提取出字符的类边缘信息,然后采用基于映射方法进行定位。实验结果表明,该方法能够准确、有效地定位和提取网络动画中的文字区域。     

基于重组DCT系数子带能量直方图的图像检索

现在许多图像采用JPEG格式存储,检索这些图像通常要先解压缩,然后提取基于像素域的特征矢量进行图像检索。己有文献提出直接在DCT域进行图像检索的方法,这样可以降低检索的时间复杂度。本文提出对JPEG图像的DCT系数利用多分辨率小波变换的形式进行重组,对整个数据库中所有图像的DCT系数重组得到的若干子带,分别建立子带能量直方图,而后采用Morton顺序建立每幅图像的索引,并采用变形B树结构组织图像数据库用于图像检索。     

基于模糊同质性映射的文本检测方法

视频图像中的文本是从语义层次对视频图像内容进行描述的非常有效信息,文本检测为基于语义的图像检索提供了条件。该文提出了一种基于模糊逻辑和同质映射相结合的文本检测方法,首先利用最大信息熵准则将原始图像模糊化;然后构造基于边缘信息和纹理信息的图像同质性,并利用它将图像映射到模糊同质性空间;最后在模糊同质性空间通过纹理分析检测文本区域。与直接在图像空间域中提取特征的文本检测方法相比,该方法对复杂背景视频图像的文本检测取得了更好的效果,并且适用于多种类型的视频图像中文本的检测。     

Data partitioning and coding of DCT coefficients based on requantization for error-resilient transmission of video

In this paper, we propose an efficient data partitioning and coding algorithm for an error-resilient transmission of DCT coefficients in error prone environment. In the typical data partitioning for Inter-coded frames, motion and macroblock header information is separated from the texture information. It can be an effective tool for the transmission of video over the error prone environment. For Intra-coded frames, however, the loss of DCT coefficients is fatal because there is no other information to reconstruct the corrupted macroblocks by errors. Conventional data partitioning algorithm for DCT coefficients is to separate a fixed number of the significant DCT coefficients from the remaining coefficients, called the spectral separation. While the spectral separation can guarantee an error resilient transmission with small overhead, the main drawback is a significant decrease in the image quality of the high priority partition, compared with that of the bitstreams without data partitioning for an equivalent bit-rate. In the proposed scheme, the quantized DCT coefficients are partitioned into an even-value approximation and the odd remainder part. We also propose a simple and efficient coding algorithm for the odd remainder part. It is shown that the proposed algorithm provides a better image quality than the conventional methods with a little overhead.     

Robust video watermarking based on affine invariant regions in the compressed domain

This paper proposes a novel robust video watermarking scheme based on local affine invariant features in the compressed domain. This scheme is resilient to geometric distortions and quite suitable for DCT-encoded compressed video data because it performs directly in the block DCTs domain. In order to synchronize the watermark, we use local invariant feature points obtained through the Harris-Affine detector which is invariant to affine distortions. To decode the frames from DCT domain to the spatial domain as fast as possible, a fast inter-transformation between block DCTs and sub-block DCTs is employed and down-sampling frames in the spatial domain are obtained by replacing each sub-blocks DCT of 2×2 pixels with half of the corresponding DC coefficient. The above-mentioned strategy can significantly save computational cost in comparison with the conventional method which accomplishes the same task via inverse DCT (IDCT). The watermark detection is performed in spatial domain along with the decoded video playing. So it is not sensitive to the video format conversion. Experimental results demonstrate that the proposed scheme is transparent and robust to signal-processing attacks, geometric distortions including rotation, scaling, aspect ratio changes, linear geometric transforms, cropping and combinations of several attacks, frame dropping, and frame rate conversion.     

Scene change detection algorithms for content-based video indexingand retrieval

There is an urgent need to extract key information from video automatically for the purposes of indexing, fast retrieval, and scene analysis. To support this vision, reliable scene change detection algorithms must be developed. Several algorithms have been proposed for both sudden and gradual scene change detection in uncompressed and compressed video. In this paper some common algorithms that have been proposed for scene change detection are reviewed. A novel algorithm for sudden scene change detection for MPEG-2 compressed video is then presented. This uses the number of interpolated macroblocks in B-frames to identify the sudden scene changes. A gradual scene change detection algorithm based on statistical features is also presented     

DCT域中MPEG7主色描述符的提取

该文在MPEG7的基础上提出了DCT域内直接提取主色描述符的新方法。这种方法节省了对图像的解压缩的过程,因而大大的提高了对于压缩图像进行特征提取的速度和效果。作为整个箅法的一部分,一种自动阈值提取的算法也在该文中给予了描述。这种方法可以减少因人为设定经验阈值而带来的不确定性,使算法更具鲁棒性。对比检索试验结果也说明本算法是一个高速有效的算法。新算法主要用于压缩图像库或互联网上的相似检索。     

基于嵌入式零树小波编码直方图图像检索

图像和视频应用的快速增长，使得根据图像和视频内容进行查询的技术变得越来越重要，人们提出了许多基于像素域或压缩域的图像检索技术，因为多媒体数据库通常具有相当大的数据量，所以基于像素域图像检索技术的计算复杂度相当大，因此，许多文献提出更快的基于压缩域的图像检索技术，本文提出一种改进的基于嵌入式零树小波编码直方图的图像检索技术，特征提取综合考虑图像的颜色，纹理，频率和空间信息，所有的特征可以在压缩过程中自动得到，图像检索的过程就是匹配待检索图像和来自数据库的侯选图像的索引，实验证明这种方法具有好的检索性能。