Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706456
Abhishek Nagar, A. Saxena, S. Bucak, Felix C. A. Fernandes, Kong-Posh Bhat
Image matching and search is gaining significant commercial importance nowadays due to various applications it enables such as augmented reality, image-queries for internet search, etc. Many researchers have effectively used color information in an image to improve its matching accuracy. These techniques, however, cannot be directly used for large scale mobile visual search applications that pose strict constraints on the size of the extracted features, computational resources and the system accuracy. To overcome this limitation, we propose a new and effective technique to incorporate color information that can use the SIFT extraction technique. We conduct our experiments on a large dataset containing around 33, 000 images that is currently being investigated in the MPEG-Compact Descriptors for Visual Search Standard and show substantial improvement compared to baseline.
如今，图像匹配和搜索正在获得重要的商业重要性，因为它可以实现各种应用，如增强现实，互联网搜索的图像查询等。许多研究者已经有效地利用图像中的颜色信息来提高图像的匹配精度。然而，这些技术不能直接用于大规模的移动视觉搜索应用，这些应用对提取特征的大小、计算资源和系统精度都有严格的限制。为了克服这一限制，我们提出了一种新的有效的技术来融合颜色信息，可以使用SIFT提取技术。我们在一个包含大约33,000张图像的大型数据集上进行实验，这些图像目前正在MPEG-Compact Descriptors for Visual Search Standard中进行研究，与基线相比显示出实质性的改进。
{"title":"Low complexity image matching using color based SIFT","authors":"Abhishek Nagar, A. Saxena, S. Bucak, Felix C. A. Fernandes, Kong-Posh Bhat","doi":"10.1109/VCIP.2013.6706456","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706456","url":null,"abstract":"Image matching and search is gaining significant commercial importance nowadays due to various applications it enables such as augmented reality, image-queries for internet search, etc. Many researchers have effectively used color information in an image to improve its matching accuracy. These techniques, however, cannot be directly used for large scale mobile visual search applications that pose strict constraints on the size of the extracted features, computational resources and the system accuracy. To overcome this limitation, we propose a new and effective technique to incorporate color information that can use the SIFT extraction technique. We conduct our experiments on a large dataset containing around 33, 000 images that is currently being investigated in the MPEG-Compact Descriptors for Visual Search Standard and show substantial improvement compared to baseline.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128703565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706354
T. Lu, R. Hu, Zhen Han, Junjun Jiang, Yanduo Zhang
Most of global face hallucination methods treat the face as a whole, ignoring the fact that the face is composed by part-based organs. Therefore, the results obtained by these methods always lack of detailed information. Nonnegative matrix factorization (NMF) based face hallucination method is properly used to enhance the detailed information. Usually, NMF basis is only learnt from high-resolution (HR) samples, leading to over-smooth output and lack of high frequency details. In order to solve this problem, we propose a simple but novel face hallucination method using nonnegative feature transformation by two-step framework. In particular, we learn the NMF basis from low-resolution (LR) and HR samples separately, and then transform the local representation feature of input into the global representation subspaces, keeping the weights into the HR samples space for output. Furthermore, the maximum a posteriori (MAP) method is used to estimate a better output. Experiments show that the hallucinated face of the proposed method is not only more high-frequency details, but also has better performance than many state-of-art algorithms.
{"title":"From local representation to global face hallucination: A novel super-resolution method by nonnegative feature transformation","authors":"T. Lu, R. Hu, Zhen Han, Junjun Jiang, Yanduo Zhang","doi":"10.1109/VCIP.2013.6706354","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706354","url":null,"abstract":"Most of global face hallucination methods treat the face as a whole, ignoring the fact that the face is composed by part-based organs. Therefore, the results obtained by these methods always lack of detailed information. Nonnegative matrix factorization (NMF) based face hallucination method is properly used to enhance the detailed information. Usually, NMF basis is only learnt from high-resolution (HR) samples, leading to over-smooth output and lack of high frequency details. In order to solve this problem, we propose a simple but novel face hallucination method using nonnegative feature transformation by two-step framework. In particular, we learn the NMF basis from low-resolution (LR) and HR samples separately, and then transform the local representation feature of input into the global representation subspaces, keeping the weights into the HR samples space for output. Furthermore, the maximum a posteriori (MAP) method is used to estimate a better output. Experiments show that the hallucinated face of the proposed method is not only more high-frequency details, but also has better performance than many state-of-art algorithms.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122970854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706379
J. Porwal
Color images are commonly represented as a combination of different components, for example, Red, Blue and Green in the RGB color space. The components are often correlated and contain common information. By representing an image in a color space in which its components are decorrelated, it can be more efficiently encoded achieving better compression. Most of the approaches to find a suitable color space for image compression are limited to transforming an n component color space to another n component color space. In this paper, we propose a novel transform that converts a 3 component RGB image to a 4 component cGST (color, gray, shade, tinge) image and vice-versa, and show its suitability for image compression. The transform is fully reversible (and hence, is suitable for lossy as well as lossless image compression) and preserves the bit-length for the GST components (allowing existing algorithms to be applied to the components). We develop an encoder-decoder tool using the transform and JPEG-LS prediction scheme, and demonstrate its efficiency (upto 35% better compression ratios over JPEG-LS, 2-5 times less runtime than JPEG 2000 with similar compression ratios) on a diverse set of test images. The transform works especially well for satellite images, computer generated animations and real images with shadows. The work also opens the scope for studying color transforms not restricted to matrix multiplication or n→n dimensional conversions for image compression. Our work also adds to the understanding of the impact of shadows on color components and is useful in image analysis in general.
{"title":"A 3D→4D color space transform for efficient lossless image compression","authors":"J. Porwal","doi":"10.1109/VCIP.2013.6706379","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706379","url":null,"abstract":"Color images are commonly represented as a combination of different components, for example, Red, Blue and Green in the RGB color space. The components are often correlated and contain common information. By representing an image in a color space in which its components are decorrelated, it can be more efficiently encoded achieving better compression. Most of the approaches to find a suitable color space for image compression are limited to transforming an n component color space to another n component color space. In this paper, we propose a novel transform that converts a 3 component RGB image to a 4 component cGST (color, gray, shade, tinge) image and vice-versa, and show its suitability for image compression. The transform is fully reversible (and hence, is suitable for lossy as well as lossless image compression) and preserves the bit-length for the GST components (allowing existing algorithms to be applied to the components). We develop an encoder-decoder tool using the transform and JPEG-LS prediction scheme, and demonstrate its efficiency (upto 35% better compression ratios over JPEG-LS, 2-5 times less runtime than JPEG 2000 with similar compression ratios) on a diverse set of test images. The transform works especially well for satellite images, computer generated animations and real images with shadows. The work also opens the scope for studying color transforms not restricted to matrix multiplication or n→n dimensional conversions for image compression. Our work also adds to the understanding of the impact of shadows on color components and is useful in image analysis in general.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123084952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706372
Xiaoliang Zhu, N. Zhang, Xiaopeng Fan, Ruiqin Xiong, Debin Zhao
One important problem in distributed video coding is to estimate the variance of the correlation noise between the video signal and its decoder side information. This variance is hard to estimate due to the lack of the motion vectors at the encoder side. In this paper, we first propose a linear model to estimate this variance by referring the zero motion prediction at the encoder based on a Markov field assumption. Furthermore, not only the prediction noise from the video signal itself but also the additional noise due to wireless transmission is considered in this paper. We applied our correlation estimation method in our recent distributed wireless visual communication framework called DCAST. The experimental results show that the proposed method improves the video PSNR by 0.5-1.5dB while avoiding motion estimation at encoder.
{"title":"Correlation estimation for distributed wireless video communication","authors":"Xiaoliang Zhu, N. Zhang, Xiaopeng Fan, Ruiqin Xiong, Debin Zhao","doi":"10.1109/VCIP.2013.6706372","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706372","url":null,"abstract":"One important problem in distributed video coding is to estimate the variance of the correlation noise between the video signal and its decoder side information. This variance is hard to estimate due to the lack of the motion vectors at the encoder side. In this paper, we first propose a linear model to estimate this variance by referring the zero motion prediction at the encoder based on a Markov field assumption. Furthermore, not only the prediction noise from the video signal itself but also the additional noise due to wireless transmission is considered in this paper. We applied our correlation estimation method in our recent distributed wireless visual communication framework called DCAST. The experimental results show that the proposed method improves the video PSNR by 0.5-1.5dB while avoiding motion estimation at encoder.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123455940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706365
Jae-Woo Kim, Jong-Ok Kim
In this paper, we propose a novel viewer state model based on gaze tracking and video content analysis. There are two primary contributions in this paper. We first improve gaze state classification significantly by combining video content analysis. Then, based on the estimated gaze state, we propose a novel viewer state model indicating both viewer's interest and existence of viewer's ROIs. Experiments were conducted to verify the performance of the proposed gaze state classifier and viewer state model. The experimental results show that the use of video content analysis in gaze state classification considerably improves the classification results and consequently, the viewer state model correctly estimates the interest state of video viewers.
{"title":"Video viewer state estimation using gaze tracking and video content analysis","authors":"Jae-Woo Kim, Jong-Ok Kim","doi":"10.1109/VCIP.2013.6706365","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706365","url":null,"abstract":"In this paper, we propose a novel viewer state model based on gaze tracking and video content analysis. There are two primary contributions in this paper. We first improve gaze state classification significantly by combining video content analysis. Then, based on the estimated gaze state, we propose a novel viewer state model indicating both viewer's interest and existence of viewer's ROIs. Experiments were conducted to verify the performance of the proposed gaze state classifier and viewer state model. The experimental results show that the use of video content analysis in gaze state classification considerably improves the classification results and consequently, the viewer state model correctly estimates the interest state of video viewers.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127154044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706394
Tran Thang Thanh, Fan Chen, K. Kotani, H. Le
With the development of the technology like 3D specialized markers, we could capture the moving signals from marker joints and create a huge set of 3D action MoCap data. The more we understand the human action, the better we could apply it to applications like security, analysis of sports, game etc. In order to find the semantically representative features of human actions, we extract the sets of action characteristics which appear frequently in the database. We then propose an Apriori-like algorithm to automatically extract the common sets shared by different action classes. The extracted representative action characteristics are defined in the semantic level, so that it better describes the intrinsic differences between various actions. In our experiments, we show that the knowledge extracted by this method achieves high accuracy of over 80% in recognizing actions on both training and testing data.
{"title":"An Apriori-like algorithm for automatic extraction of the common action characteristics","authors":"Tran Thang Thanh, Fan Chen, K. Kotani, H. Le","doi":"10.1109/VCIP.2013.6706394","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706394","url":null,"abstract":"With the development of the technology like 3D specialized markers, we could capture the moving signals from marker joints and create a huge set of 3D action MoCap data. The more we understand the human action, the better we could apply it to applications like security, analysis of sports, game etc. In order to find the semantically representative features of human actions, we extract the sets of action characteristics which appear frequently in the database. We then propose an Apriori-like algorithm to automatically extract the common sets shared by different action classes. The extracted representative action characteristics are defined in the semantic level, so that it better describes the intrinsic differences between various actions. In our experiments, we show that the knowledge extracted by this method achieves high accuracy of over 80% in recognizing actions on both training and testing data.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127928523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706376
Fanman Meng, Bing Luo, Chao Huang
In this paper, we develop a new algorithm to segment multiple common objects from a group of images. Our method consists of two aspects: directed graph clustering and prior propagation. The clustering is used to cluster the local regions of the original images and generate the foreground priors from these clusterings. The second step propagates the prior of each class and locates the common objects from the images in terms of foreground map. Finally, we use the foreground map as the unary term of Markov random field segmentation and segment the common objects by graph-cuts algorithm. We test our method on FlickrMFC and ICoseg datasets. The experimental results show that the proposed method can achieve larger accuracy compared with several state-of-arts co-segmentation methods.
{"title":"Object co-segmentation based on directed graph clustering","authors":"Fanman Meng, Bing Luo, Chao Huang","doi":"10.1109/VCIP.2013.6706376","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706376","url":null,"abstract":"In this paper, we develop a new algorithm to segment multiple common objects from a group of images. Our method consists of two aspects: directed graph clustering and prior propagation. The clustering is used to cluster the local regions of the original images and generate the foreground priors from these clusterings. The second step propagates the prior of each class and locates the common objects from the images in terms of foreground map. Finally, we use the foreground map as the unary term of Markov random field segmentation and segment the common objects by graph-cuts algorithm. We test our method on FlickrMFC and ICoseg datasets. The experimental results show that the proposed method can achieve larger accuracy compared with several state-of-arts co-segmentation methods.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121273480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706355
Catherine Soladié, R. Séguier, Nicolas Stoiber
This paper proposes a new method for the analysis of blended expressions with varying intensity. The method is based on an asymmetric bilinear model learned on a small amount of expressions. In the resulting expression space, a blended unknown expression has a signature, that can be interpreted as a mixture of the basic expressions used in the creation of the space. Three methods are compared: a traditional method based on active appearance vectors, the asymmetric bilinear model on person-independent appearance vectors and the asymmetric bilinear model on person-specific appearance vectors. Experimental results on the recognition of 14 blended unknown expressions show the relevance of the bilinear models compared to appearance-based methods and the robustness of the person-specific models according to the types of parameters (shape and/or texture).
{"title":"Bilinear decomposition for blended expressions representation","authors":"Catherine Soladié, R. Séguier, Nicolas Stoiber","doi":"10.1109/VCIP.2013.6706355","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706355","url":null,"abstract":"This paper proposes a new method for the analysis of blended expressions with varying intensity. The method is based on an asymmetric bilinear model learned on a small amount of expressions. In the resulting expression space, a blended unknown expression has a signature, that can be interpreted as a mixture of the basic expressions used in the creation of the space. Three methods are compared: a traditional method based on active appearance vectors, the asymmetric bilinear model on person-independent appearance vectors and the asymmetric bilinear model on person-specific appearance vectors. Experimental results on the recognition of 14 blended unknown expressions show the relevance of the bilinear models compared to appearance-based methods and the robustness of the person-specific models according to the types of parameters (shape and/or texture).","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126316951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706413
Wan Wang, Xinghao Jiang, Shilin Wang, Tanfeng Sun
The advanced technology and sophisticated software have rendered audiovisual content exposed to forgery, inspiring the emergence of multimedia forensic research. Since video tampering may involve double compression, the analysis of compression history is of significance. In this paper, we consider the processing chains of two compression steps and propose an algorithm that aims at identifying the quantization parameter used in the previous coding process. The method relies on the fact that characteristic footprints can be observed under different relationships between quantization parameters of consecutive compression operations. Features are extracted from both Discrete Cosine Transform (DCT) coefficients and their differential counterparts to capture the statistical disturbance. Experimental results demonstrate the effectiveness of our method.
{"title":"Estimation of the primary quantization parameter in MPEG videos","authors":"Wan Wang, Xinghao Jiang, Shilin Wang, Tanfeng Sun","doi":"10.1109/VCIP.2013.6706413","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706413","url":null,"abstract":"The advanced technology and sophisticated software have rendered audiovisual content exposed to forgery, inspiring the emergence of multimedia forensic research. Since video tampering may involve double compression, the analysis of compression history is of significance. In this paper, we consider the processing chains of two compression steps and propose an algorithm that aims at identifying the quantization parameter used in the previous coding process. The method relies on the fact that characteristic footprints can be observed under different relationships between quantization parameters of consecutive compression operations. Features are extracted from both Discrete Cosine Transform (DCT) coefficients and their differential counterparts to capture the statistical disturbance. Experimental results demonstrate the effectiveness of our method.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125562930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1109/VCIP.2013.6706364
Geert Braeckman, Shahid M. Satti, Heng Chen, A. Munteanu, P. Schelkens
This paper presents a novel two-layer coding framework targeting visually lossless compression of screen content video. The proposed framework employs the conventional HEVC standard for the base-layer. For the enhancement layer, a hybrid of spatial and temporal block-prediction mechanism is introduced to guarantee a small energy of the error-residual. Spatial prediction is generally chosen for dynamic areas, while temporal predictions yield better prediction for static areas in a video frame. The prediction residual is quantized based on whether a given block is static or dynamic. Run-length coding, Golomb based binarization and context-based arithmetic coding are employed to efficiently code the quantized residual and form the enhancement-layer. Performance evaluations using 4:4:4 screen content sequences show that, for visually lossless video quality, the proposed system significantly saves the bit-rate compared to the two-layer lossless HEVC framework.
{"title":"Visually lossless screen content coding using HEVC base-layer","authors":"Geert Braeckman, Shahid M. Satti, Heng Chen, A. Munteanu, P. Schelkens","doi":"10.1109/VCIP.2013.6706364","DOIUrl":"https://doi.org/10.1109/VCIP.2013.6706364","url":null,"abstract":"This paper presents a novel two-layer coding framework targeting visually lossless compression of screen content video. The proposed framework employs the conventional HEVC standard for the base-layer. For the enhancement layer, a hybrid of spatial and temporal block-prediction mechanism is introduced to guarantee a small energy of the error-residual. Spatial prediction is generally chosen for dynamic areas, while temporal predictions yield better prediction for static areas in a video frame. The prediction residual is quantized based on whether a given block is static or dynamic. Run-length coding, Golomb based binarization and context-based arithmetic coding are employed to efficiently code the quantized residual and form the enhancement-layer. Performance evaluations using 4:4:4 screen content sequences show that, for visually lossless video quality, the proposed system significantly saves the bit-rate compared to the two-layer lossless HEVC framework.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129766126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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