Space-borne equipments produce very big images while their capacities of storage, calculation and transmission are limited, so low-complexity image compression algorithms are necessary. In this paper, we develop an ef...
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Space-borne equipments produce very big images while their capacities of storage, calculation and transmission are limited, so low-complexity image compression algorithms are necessary. In this paper, we develop an efficient image compression algorithm based on quadtree in wavelet domain for this mission. First, we propose an adaptive scanning order for quadtree, which traverses prior the neighbors of previous significant nodes from bottom to the top of quadtree, so that more significant coefficients are encoded at a specified bit rate. Second, we divide the entire wavelet image to several blocks and encode them individually. Because the distortion-rate usually decreases as the level of the quadtree increases with the adaptive scanning order, to control bit rate for each block, we set the points exactly after coding each level of the quadtree as the candidate truncation points. The proposed method can provide quality, position and resolution scalability, which is simple and fast without any entropy coding, so it is very suitable for space-borne equipments. Experimental results show that it attains better performance compared with some state-of-the-art algorithms.
Inprobability model based rate control of video coding, modeling of residual distribution is important in predicting precise distortions so as to determine appropriate quantization parameter values. For this, single p...
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Inprobability model based rate control of video coding, modeling of residual distribution is important in predicting precise distortions so as to determine appropriate quantization parameter values. For this, single probability model approaches have been popularly taken which may fail to model the underlying statistical characteristics of different residues from variable block-sized coding. In this letter, new rate and distortion models based on a mixture of multiple Laplacian distributions are presented for the transform coefficients of inter-predicted residues in quadtree coding. The proposed mixture model of multiple Laplacian distributions is tested for the High Efficiency Video coding (HEVC) Test Model (HM) with quadtree-structured coding Unit and Transform Unit. The experimental results show that the proposed model achieves more accurate results of rate and distortion estimation than the single probability models.
A lossless compression algorithm for synthetic aperture radar (SAR) amplitude images based on modified quadtree bit-plane coding is proposed. First, a SAR amplitude image is divided into independent bit planes, and th...
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A lossless compression algorithm for synthetic aperture radar (SAR) amplitude images based on modified quadtree bit-plane coding is proposed. First, a SAR amplitude image is divided into independent bit planes, and then, the probability of bit "0" is computed and compared with the predefined threshold in order to select the optimal block size for each bit plane. Finally, a modified quadtree coding method is adopted to encode each block data. Additionally, the computing method of predefined threshold is also addressed in this letter. The experimental results show that the proposed method outperforms previous methods for all SAR images of the test sets;an average 0.895-bpp decrease in bit rate was observed when compared with JPEG-LS.
In this paper, a novel distortion model based on a mixture of Laplacian distributions is presented for the transform coefficients of predicted residues in quadtree coding. The mixture Laplacian distribution is made on...
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ISBN:
(纸本)9780819489524
In this paper, a novel distortion model based on a mixture of Laplacian distributions is presented for the transform coefficients of predicted residues in quadtree coding. The mixture Laplacian distribution is made on the coding structure with different quadtree coding unit (CU) depth. Moreover, for intra-coded CU, the distortion model is asymptotically simplified based on the signal characteristics of the transform coefficient. The proposed mixture model of multiple Laplacian distributions is tested for the High Efficiency Video coding (HEVC) Test Model (HM) with quadtree-structured coding Unit (CU) and Transform Unit (TU). The experimental results show that the proposed model achieves more accurate results of distortion estimation than the single probability models.
Due to the limitations of storage and transmission in remote sensing scenarios, lossy compression techniques have been commonly considered for remote sensing images. Inspired by the latest development in image coding ...
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Due to the limitations of storage and transmission in remote sensing scenarios, lossy compression techniques have been commonly considered for remote sensing images. Inspired by the latest development in image coding techniques, we present in this paper a new compression framework, which combines the directional adaptive lifting partitioned block transform (DAL-PBT) with content-driven quadtree codec with optimized truncation (CQOT). First, the DAL-PBT model is designed;it calculates the optimal prediction directions of each image block and performs the weighted directional adaptive interpolation during the process of directional lifting. Secondly, the CQOT method is proposed, which provides different scanning orders among and within blocks based on image content, and encodes those blocks with a quadtree codec with optimized truncation. The two phases are closely related: the former is devoted to image representation for preserving more directional information of remote sensing images, and the latter leverages adaptive scanning on the transformed image blocks to further improve coding efficiency. The proposed method supports various progressive transmission modes. Experimental results show that the proposed method outperforms not only the mainstream compression methods, such as JPEG2000 and CCSDS, but also, in terms of some evaluation indexes, some state-of-the-art compression methods presented recently.
Video quality estimation is considered a means of monitoring quality of service in broadcasting or IPTV services. In this paper, a no-reference peak signal-to-noise ratio (PSNR) estimation method is first presented fo...
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Video quality estimation is considered a means of monitoring quality of service in broadcasting or IPTV services. In this paper, a no-reference peak signal-to-noise ratio (PSNR) estimation method is first presented for a quadtree-based motion estimation or compensation and transform coding scheme such as HEVC test model (HM), which is expected to be popularly used due to its highly enhanced coding efficiency, in 2-D and 3-D high resolution videos. The proposed no-reference PSNR estimation method is based on a Laplacian mixture distribution, which takes into account the distribution characteristics of residual transform coefficients in different quadtree depths and coding types of coding units (CUs). In order to predict the model parameters of the Laplacian mixture distribution for all zero quantized coefficients case, an exponential regression scheme is employed over quadtree depth levels of CUs. The proposed no-reference PSNR estimation method yields fairly accurate results from 0.970 to 0.983 in correlation and from 0.530 to 0.890 in RMSE between the actual and the estimated PSNR values for HM encoded bitstreams, outperforming single PDF based models.
Several techniques based on the three-dimensional (3-D) discrete cosine, transform, (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolu...
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Several techniques based on the three-dimensional (3-D) discrete cosine, transform, (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview, of several state-of-the-art 3-D, wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts;layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.
This paper presents a novel still image compression scheme that extends the traditional JPEG standard with lossy-to-lossless compression support. The system follows a two-layer design approach which allows for backwar...
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ISBN:
(纸本)9781479923410
This paper presents a novel still image compression scheme that extends the traditional JPEG standard with lossy-to-lossless compression support. The system follows a two-layer design approach which allows for backward compatibility with the conventional JPEG standard for the base layer and provides lossless compression when decoding the enhancement layer. The system employs several coding tools, including quadtree coding, spatial domain prediction, reversible discrete cosine transforms, and context-based arithmetic coding to efficiently encode losslessly the enhancement layer. Performance evaluations using a standard JPEG set of images show that the proposed system yields similar lossless compression performance to the state-of-the-art single-layer JPEG-LS standard while providing quality scalability and a JPEG-compatible base layer at the same time.
This paper proposes the texture-based coding unit (CU) size decision (TBCUD) algorithm that includes texture based block partitioning. While the existing algorithm calculates every CU size, the proposed algorithm only...
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ISBN:
(纸本)9781509015702
This paper proposes the texture-based coding unit (CU) size decision (TBCUD) algorithm that includes texture based block partitioning. While the existing algorithm calculates every CU size, the proposed algorithm only considers the determined CU sizes that are decided by the texture of the image. Because the prediction is performed by the prediction unit (PU) derived from CU, the proposed algorithm can reduce the encoding time by skipping the unnecessary computation. Experimental results show that the proposed algorithm can reduce the average encoding time by 47.21 % at a cost of 2.55% bit rate increase compared to the high efficiency video coding (HEVC) Test Model (HM) 14.0.
This paper presents a novel still image compression scheme that extends the traditional JPEG standard with lossy-to-lossless compression support. The system follows a two-layer design approach which allows for backwar...
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ISBN:
(纸本)9781479923427
This paper presents a novel still image compression scheme that extends the traditional JPEG standard with lossy-to-lossless compression support. The system follows a two-layer design approach which allows for backward compatibility with the conventional JPEG standard for the base layer and provides lossless compression when decoding the enhancement layer. The system employs several coding tools, including quadtree coding, spatial domain prediction, reversible discrete cosine transforms, and context-based arithmetic coding to efficiently encode losslessly the enhancement layer. Performance evaluations using a standard JPEG set of images show that the proposed system yields similar lossless compression performance to the state-of-the-art single-layer JPEG-LS standard while providing quality scalability and a JPEG-compatible base layer at the same time.
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