Applications such as wireless displays, automotive infotainment, remote desktop, remote gaming, distance education, cloud computing etc. are becoming popular. Video in these applications often has mixed content consis...
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Applications such as wireless displays, automotive infotainment, remote desktop, remote gaming, distance education, cloud computing etc. are becoming popular. Video in these applications often has mixed content consisting of natural video and screen content (text, graphics etc.) in the same picture. In text and graphics regions, patterns such as text characters, icons, lines etc. can repeat within a picture. Also since the graphics and text regions have sharp edges that are sometimes not predicted well by Intra prediction tools, the probability of prediction error having high amplitude increases. This paper presents two tools for improving the intra coding efficiency of the High Efficiency Video coding (HEVC) standard when coding screen content. The first tool is a coding Unit (CU)-level Intra motion compensation tool to eliminate redundancy from repeating patterns in text and graphics regions. The second tool is a modification to HEVC cRiceParam update process of coeff_abs_level_remaining entropy coding to adapt better to larger prediction errors in text and graphics regions. The combination of the two tools achieves an average bit-rate/Bjontegaard Delta-Rate savings in the range of 0.8% to 28.1% over HEVC Range Extensions Test Model on screen content test video sequences used in Range Extensions core experiments by the Joint Collaborative Team for Video coding (JCT-VC).
Correlated steganography considers the case in which the cover work is chosen to be correlated with the covert message that is to be hidden. The advantage of this is that, at least theoretically, the number of bits ne...
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Correlated steganography considers the case in which the cover work is chosen to be correlated with the covert message that is to be hidden. The advantage of this is that, at least theoretically, the number of bits needed to encode the hidden message can be considerably reduced since it is based on the conditional entropy of the message given the cover. This may be much less than the entropy of the message itself. And if the number of bits needed to embed the hidden message is significantly reduced, then it is more likely that the steganographic algorithm will be secure, i.e. undetectable. In this paper, we describe an example of correlated steganography. Specifically, we are interested in embedding a covert image into a cover image. Comparative experiments indicate that selecting a cover Work that is correlated with the covert message can reduce the number of bits needed to represent the covert image below that needed by standard JPEG compression, provided the two images are sufficiently correlated.
We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-base...
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We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients.
In this paper, we present a rare-distortion (R-D) based bit allocation scheme for MPEG-4 zerotree entropy based wavelet coding, specifically, the Multiscale Zerotree entropy coding mode (MQ) of MPEG-4 Visual Texture C...
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In this paper, we present a rare-distortion (R-D) based bit allocation scheme for MPEG-4 zerotree entropy based wavelet coding, specifically, the Multiscale Zerotree entropy coding mode (MQ) of MPEG-4 Visual Texture coding tool. With an iterative quadratic R-D model, our algorithm achieves accurate target bitrate and better image quality with fast convergence.
Direct VLSI implementation of context-based adaptive variable length coding (CAVLC) for residues, as a modification from conventional run-length coding, will lead to low throughput and utilization. In this paper, an e...
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ISBN:
(纸本)0780390601
Direct VLSI implementation of context-based adaptive variable length coding (CAVLC) for residues, as a modification from conventional run-length coding, will lead to low throughput and utilization. In this paper, an efficient CAVLC design is proposed. The main concept is the two-stage block pipelining scheme for parallel processing of two 4/spl times/4-blocks. When one block is processed by the scanning engine to collect the required symbols, its previous block is handled by the coding engine to translate symbols into bitstream. The dual-block-pipelined architecture doubles the throughput and utilization of CAVLC at high bitrates. Moreover, a zero skipping technique is adopted to reduce up to 90% of cycles at low bitrates. Last but not least, exponential-Golomb coding for other general symbols and bitstream encapsulation for network abstraction layer are integrated with CAVLC engine as a complete entropy coder for H.264/AVC baseline profile. Simulation results show that our design is capable of real-time processing for 1920 /spl times/ 1088 30fps videos with 23.6K logic gates at 100MHz.
A new efficient image coding scheme, based on quadtree representation and block entropy coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated ...
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ISBN:
(纸本)0818679190
A new efficient image coding scheme, based on quadtree representation and block entropy coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated into the quantization process. In addition, how to flexibly control the quantization level as well as output bitrate of the coder is also investigated. The coding efficiency of the coder is quite competitive with the well-known EZW coder, and requires less computation burden. The proposed coding scheme can also be applied in image sequence coding, resulting in satisfactory performance.
A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstru...
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ISBN:
(纸本)9781467300469
A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstruction points, we can prune the tree to control the distortion of the quantizer. Our results show the proposed method improves existing similar work and significantly outperforms scalable coding based on reconstruction error quantization as used in practical systems, eg. MPEG-4 audio.
The Adaptive Multirate (AMR) speech codec operates in 8 different fixed-rate modes. In every mode, it uses a specified number of bits to quantize and encode the current speech frame. It encodes the spectral envelope b...
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The Adaptive Multirate (AMR) speech codec operates in 8 different fixed-rate modes. In every mode, it uses a specified number of bits to quantize and encode the current speech frame. It encodes the spectral envelope by means of Line Spectral Frequencies (LSF) parameters, by using the constrained resolution (CR) fixed-rate Split Matrix Quantization (SMQ) and Split Vector Quantization (SVQ) methods. However, by using the Gaussian Mixture Model (GMM) based transform coding technique, the quantization of the spectral envelope can be significantly improved in the spectral distortion (SD) sense. This technique involves adaptive decorrelation of the LSF vectors by applying an orthogonal linear transformation combined with an ordinary scalar quantization of the decorrelated vector's components. We apply uniform scalar quantization followed by entropy constrained (EC) coding as it appears to be generally more efficient than non-uniform scalar quantizers. This paper describes the techniques used to adapt the entropy coded variable bit-rate output bit strings to the AMR codec modes using fixed-rate output bit strings. In order to constrain the length of the code, we use variable quantization step size and vector truncation techniques. Their application aspects are thoroughly investigated and described in this paper.
A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstru...
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A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstruction points, we can prune the tree to control the distortion of the quantizer. Our results show the proposed method improves existing similar work and significantly outperforms scalable coding based on reconstruction error quantization as used in practical systems, eg. MPEG-4 audio.
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