In this paper we propose a fast candidate selection method in RMD step of Intra prediction. The proposed method consist of two steps, in the first step, coarser steps between the prediction directions are used as possible candidates for comparison, where the coarser step size is a function of Prediction Unit size. This way we find the dominant direction with minimum cost. In the second step, the dominant direction is refined by checking the prediction directions around the dominant direction to find the best match.
{"title":"A Method for Fast Rough Mode Decision in HEVC","authors":"Manoj Alwani, S. Johar","doi":"10.1109/DCC.2013.58","DOIUrl":"https://doi.org/10.1109/DCC.2013.58","url":null,"abstract":"In this paper we propose a fast candidate selection method in RMD step of Intra prediction. The proposed method consist of two steps, in the first step, coarser steps between the prediction directions are used as possible candidates for comparison, where the coarser step size is a function of Prediction Unit size. This way we find the dominant direction with minimum cost. In the second step, the dominant direction is refined by checking the prediction directions around the dominant direction to find the best match.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126985586","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}
Philipp Helle, H. Lakshman, Mischa Siekmann, J. Stegemann, Tobias Hinz, H. Schwarz, D. Marpe, T. Wiegand
The paper describes a scalable video coding extension of the upcoming HEVC video coding standard for spatial and quality scalable coding. Besides coding tools known from scalable profiles of prior video coding standards, it includes new coding tools that further improve the enhancement layer coding efficiency. The effectiveness of the proposed scalable HEVC extension is demonstrated by comparing the coding efficiency to simulcast and single-layer coding for several test sequences and coding conditions.
{"title":"A Scalable Video Coding Extension of HEVC","authors":"Philipp Helle, H. Lakshman, Mischa Siekmann, J. Stegemann, Tobias Hinz, H. Schwarz, D. Marpe, T. Wiegand","doi":"10.1109/DCC.2013.28","DOIUrl":"https://doi.org/10.1109/DCC.2013.28","url":null,"abstract":"The paper describes a scalable video coding extension of the upcoming HEVC video coding standard for spatial and quality scalable coding. Besides coding tools known from scalable profiles of prior video coding standards, it includes new coding tools that further improve the enhancement layer coding efficiency. The effectiveness of the proposed scalable HEVC extension is demonstrated by comparing the coding efficiency to simulcast and single-layer coding for several test sequences and coding conditions.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114404162","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}
In this paper, we propose an efficient image super-resolution algorithm based on hierarchical and collaborative sparse representation (HCSR). Motivated by the observation that natural images typically exhibit multi-modal statistics, we propose a hierarchical sparse coding model which includes two layers: the first layer encodes individual patches, and the second layer jointly encodes the set of patches that belong to the same homogeneous subset of image space. We further present a simple alternative to achieve such target by identifying optimal sparse representation that is adaptive to specific statistics of images. Specially, we cluster images from the offline training set into regions of similar geometric structure, and model each region (cluster) by learning adaptive bases describing the patches within that cluster using principal component analysis (PCA). This cluster-specific dictionary is then exploited to optimally estimate the underlying HR pixel values using the idea of collaborative sparse coding, in which the similarity between patches in the same cluster is further considered. It conceptually and computationally remedies the limitation of many existing algorithms based on standard sparse coding, in which patches are independently encoded. Experimental results demonstrate the proposed method appears to be competitive with state-of-the-art algorithms.
{"title":"Image Super-Resolution via Hierarchical and Collaborative Sparse Representation","authors":"Xianming Liu, Deming Zhai, Debin Zhao, Wen Gao","doi":"10.1109/DCC.2013.17","DOIUrl":"https://doi.org/10.1109/DCC.2013.17","url":null,"abstract":"In this paper, we propose an efficient image super-resolution algorithm based on hierarchical and collaborative sparse representation (HCSR). Motivated by the observation that natural images typically exhibit multi-modal statistics, we propose a hierarchical sparse coding model which includes two layers: the first layer encodes individual patches, and the second layer jointly encodes the set of patches that belong to the same homogeneous subset of image space. We further present a simple alternative to achieve such target by identifying optimal sparse representation that is adaptive to specific statistics of images. Specially, we cluster images from the offline training set into regions of similar geometric structure, and model each region (cluster) by learning adaptive bases describing the patches within that cluster using principal component analysis (PCA). This cluster-specific dictionary is then exploited to optimally estimate the underlying HR pixel values using the idea of collaborative sparse coding, in which the similarity between patches in the same cluster is further considered. It conceptually and computationally remedies the limitation of many existing algorithms based on standard sparse coding, in which patches are independently encoded. Experimental results demonstrate the proposed method appears to be competitive with state-of-the-art algorithms.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114811129","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}
This paper is devoted to Sample Adaptive Offset (SAO). This technique was recently added into High Efficiency Video Coding (HEVC) standard. The concept of SAO is to reduce sample distortion of a region by classifying the region samples into multiple categories, obtaining an offset for each category, and then adding the offset to each sample, where the classifier index and the offsets are coded in the bit stream.
{"title":"Sample Adaptive Offset Design in HEVC","authors":"A. Alshin, E. Alshina, Jeonghoon Park","doi":"10.1109/DCC.2013.57","DOIUrl":"https://doi.org/10.1109/DCC.2013.57","url":null,"abstract":"This paper is devoted to Sample Adaptive Offset (SAO). This technique was recently added into High Efficiency Video Coding (HEVC) standard. The concept of SAO is to reduce sample distortion of a region by classifying the region samples into multiple categories, obtaining an offset for each category, and then adding the offset to each sample, where the classifier index and the offsets are coded in the bit stream.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124746306","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}
Feng Chen, M. Rutkowski, Christopher Fenner, R. Huck, Shuang Wang, Samuel Cheng
Summary form only given. Distributed Source Coding (DSC) is rapidly gaining popularity, and has many good applications. However, some important correlations are sometimes omitted, such as temporal correlation. In this paper, we consider the correlations of the source data both in spatial and temporal domains for DSC decoding. And this is equally to integrate a Kalman filter in our algorithm. We tested our algorithm on the practical temperature network, and the results turn out it achieved better performance than the algorithm without temporal correlation.
{"title":"Compression of Distributed Correlated Temperature Data in Sensor Networks","authors":"Feng Chen, M. Rutkowski, Christopher Fenner, R. Huck, Shuang Wang, Samuel Cheng","doi":"10.1109/DCC.2013.61","DOIUrl":"https://doi.org/10.1109/DCC.2013.61","url":null,"abstract":"Summary form only given. Distributed Source Coding (DSC) is rapidly gaining popularity, and has many good applications. However, some important correlations are sometimes omitted, such as temporal correlation. In this paper, we consider the correlations of the source data both in spatial and temporal domains for DSC decoding. And this is equally to integrate a Kalman filter in our algorithm. We tested our algorithm on the practical temperature network, and the results turn out it achieved better performance than the algorithm without temporal correlation.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124685677","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}
In its Paris meeting, the JPEG committee decided to work on a backwards compatible extension of the popular JPEG (10918-1) standard enabling lossy and lossless coding of high-dynamic range (HDR) images, the new standard shall allow legacy applications to decompress new code streams into a tone mapped version of the HDR image while codecs aware of the extensions will decompress the stream with full dynamic range. This paper proposes a set of extensions that have rather low implementation complexity, and use - whenever possible - functional design blocks already present in 10918-1. It is seen that, despite its simplicity, the proposed extension performs close to JPEG 2000 (15444-2) and JPEG XR (29199-2) on the HDR test image set of the JPEG for high bit-rates.
{"title":"Backwards Compatible Coding of High Dynamic Range Images with JPEG","authors":"T. Richter","doi":"10.1109/DCC.2013.24","DOIUrl":"https://doi.org/10.1109/DCC.2013.24","url":null,"abstract":"In its Paris meeting, the JPEG committee decided to work on a backwards compatible extension of the popular JPEG (10918-1) standard enabling lossy and lossless coding of high-dynamic range (HDR) images, the new standard shall allow legacy applications to decompress new code streams into a tone mapped version of the HDR image while codecs aware of the extensions will decompress the stream with full dynamic range. This paper proposes a set of extensions that have rather low implementation complexity, and use - whenever possible - functional design blocks already present in 10918-1. It is seen that, despite its simplicity, the proposed extension performs close to JPEG 2000 (15444-2) and JPEG XR (29199-2) on the HDR test image set of the JPEG for high bit-rates.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121322588","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}
Robson Lins, Diogo B. Henriques, Emerson Lima, Silvio Melo
This work presents a fast block matching method for motion estimation algorithms by using low discrepancy sequences. The proposed technique (VDHS) was developed after analyzing the UMHS algorithm implemented within the H.264/AVC Reference Software. The optimizations are focused both in the reduction of the number of candidate blocks and the usage of pixel sub sampling based on VDH in order to accelerate SAD's computation. Experimental results show that the proposed technique has a lower computational effort with an insignificant loss on PSNR and slight increment on the bit-rate.
{"title":"VDH-Grid Search Algorithm for Fast Motion Estimation","authors":"Robson Lins, Diogo B. Henriques, Emerson Lima, Silvio Melo","doi":"10.1109/DCC.2013.86","DOIUrl":"https://doi.org/10.1109/DCC.2013.86","url":null,"abstract":"This work presents a fast block matching method for motion estimation algorithms by using low discrepancy sequences. The proposed technique (VDHS) was developed after analyzing the UMHS algorithm implemented within the H.264/AVC Reference Software. The optimizations are focused both in the reduction of the number of candidate blocks and the usage of pixel sub sampling based on VDH in order to accelerate SAD's computation. Experimental results show that the proposed technique has a lower computational effort with an insignificant loss on PSNR and slight increment on the bit-rate.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126016007","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}
In literature decoder-side motion estimation is shown to improve video coding efficiency of both H.264 and HEVC standards. In this paper we introduce enhanced skip and direct modes for H.264 coding using decoder-side super-resolution (SR) and frame interpolation. P- and B-frames are down sampled and H.264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Alternatively for B-frames, bidirectional true motion estimation is performed to synthesize a B-frame from its reference frames. For P-frames, bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm determines for each MB which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.04 dB PSNR improvement or 23.0% bit rate reduction at low bit rates when compared to H.264 standard. Average PSNR gains reach as high as 3.95 dB depending on the video content and frame rate.
{"title":"Decoder-Side Super-Resolution and Frame Interpolation for Improved H.264 Video Coding","authors":"H. Ateş","doi":"10.1109/DCC.2013.16","DOIUrl":"https://doi.org/10.1109/DCC.2013.16","url":null,"abstract":"In literature decoder-side motion estimation is shown to improve video coding efficiency of both H.264 and HEVC standards. In this paper we introduce enhanced skip and direct modes for H.264 coding using decoder-side super-resolution (SR) and frame interpolation. P- and B-frames are down sampled and H.264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Alternatively for B-frames, bidirectional true motion estimation is performed to synthesize a B-frame from its reference frames. For P-frames, bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm determines for each MB which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.04 dB PSNR improvement or 23.0% bit rate reduction at low bit rates when compared to H.264 standard. Average PSNR gains reach as high as 3.95 dB depending on the video content and frame rate.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127093984","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}
The computational performance of recent processors is often restricted by the delay of off-chip memory accesses, and so low-delay data compression should be effective to improve the processor performance. This paper proposes differential base pattern coding suitable for high-speed parallel decoding. Evaluation shows that the compression ratio of the coding is comparable or superior to that of conventional codings.
{"title":"Differential Base Pattern Coding for Cache Line Data Compression","authors":"H. Kaneko, S. Fujii, Hiroaki Sasaki","doi":"10.1109/DCC.2013.79","DOIUrl":"https://doi.org/10.1109/DCC.2013.79","url":null,"abstract":"The computational performance of recent processors is often restricted by the delay of off-chip memory accesses, and so low-delay data compression should be effective to improve the processor performance. This paper proposes differential base pattern coding suitable for high-speed parallel decoding. Evaluation shows that the compression ratio of the coding is comparable or superior to that of conventional codings.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126928767","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}
Rui Zhong, R. Hu, Zhongyuan Wang, Lu Liu, Zhen Han
The multi-view video plus depth (MVD) format has been put forward for the call for proposals in free view video (FVV) and 3DTV. Since representing the 3D scene geometry, depth maps are used for synthesizing virtual views. However, compression artifacts of the depth images always lead to geometry distortions in synthesized views. By exploiting LBP features of the corresponding color samples, we propose a novel local binary pattern (LBP) guided depth filter which enables the local neighborhood samples those are in the same object of the current pixel to be filtering input. In recognition of its ability for describing the object edges, the LBP operator is used to calculate the weighted values of the local depth pixels for the depth-map filter. Furthermore, the filter is incorporated into the framework of H.264/MVC as an in-loop filter. The experimental results demonstrate that the proposed approach offers 0.45dB and 0.66dB average PSNR gains in terms of video rendering quality and depth coding efficiency, as well as significant subjective improvement in rendering views.
{"title":"LBP-Guided Depth Image Filter","authors":"Rui Zhong, R. Hu, Zhongyuan Wang, Lu Liu, Zhen Han","doi":"10.1109/DCC.2013.115","DOIUrl":"https://doi.org/10.1109/DCC.2013.115","url":null,"abstract":"The multi-view video plus depth (MVD) format has been put forward for the call for proposals in free view video (FVV) and 3DTV. Since representing the 3D scene geometry, depth maps are used for synthesizing virtual views. However, compression artifacts of the depth images always lead to geometry distortions in synthesized views. By exploiting LBP features of the corresponding color samples, we propose a novel local binary pattern (LBP) guided depth filter which enables the local neighborhood samples those are in the same object of the current pixel to be filtering input. In recognition of its ability for describing the object edges, the LBP operator is used to calculate the weighted values of the local depth pixels for the depth-map filter. Furthermore, the filter is incorporated into the framework of H.264/MVC as an in-loop filter. The experimental results demonstrate that the proposed approach offers 0.45dB and 0.66dB average PSNR gains in terms of video rendering quality and depth coding efficiency, as well as significant subjective improvement in rendering views.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131319084","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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