The Experts below are selected from a list of 50403 Experts worldwide ranked by ideXlab platform
Akira Kurematsu - One of the best experts on this subject based on the ideXlab platform.
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generalized unequal length lapped orthogonal transform for subband Image Coding
IEEE Transactions on Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:Generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOTs) are considered. The length of each basis of the proposed GULLOT can be different from each other, whereas all the bases of the conventional GenLOT are of equal length. In general, for Image Coding application, the long basis for a low-frequency band and the short basis for a high-frequency one are desirable to reduce the blocking and the ringing artifact simultaneously. Therefore, the GULLOT is suitable especially for a subband Image Coding. In order to apply the GULLOT to a subband Image Coding, we also investigate the size-limited structure to process the finite length signal, which is important in practice. Finally, some design and Image Coding examples are shown to confirm the validity of the proposed GULLOT.
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generalized unequal length lapped orthogonal transform for subband Image Coding
International Conference on Acoustics Speech and Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:In this paper, generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOT) are considered. The length of each basis of the proposed GULLOT can be different from each other, while all the bases of the conventional GenLOT are of equal length. In order to apply the GULLOT to subband Image Coding, we also investigate the size-limited structure to process the finite length signal which is important in practice.
Taizo Suzuki - One of the best experts on this subject based on the ideXlab platform.
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generalized block lifting factorization of m channel biorthogonal filter banks for lossy to lossless Image Coding
IEEE Transactions on Image Processing, 2012Co-Authors: Taizo Suzuki, Masaaki Ikehara, T Q NguyenAbstract:Generalized block-lifting factorization of M-channel (M >; 2) biorthogonal filter banks (BOFBs) for lossy-to-lossless Image Coding is presented in this paper. Since the proposed block-lifting structure is more general than the conventional lifting factorizations and does NOT require many restrictions such as paraunitary, number of channels, and McMillan degree in each building block unlike the conventional lifting factorizations, its Coding gain is higher than that of the previous methods. Several proposed BOFBs are designed and applied to Image Coding. Comparing the results with conventional lossy-to-lossless Image Coding structures, including the 5/3- and 9/7-tap discrete wavelet transforms in JPEG 2000 and a 4 × 8 hierarchical lapped biorthogonal transform in JPEG XR, the proposed BOFBs achieve better result in both objective measure and perceptual visual quality for the Images with a lot of high-frequency components.
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integer fast lapped orthogonal transform based on direct lifting of dcts for lossless to lossy Image Coding
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Taizo SuzukiAbstract:Integer lapped orthogonal transforms (LOTs) are vital technologies for the unification of lossless and lossy Image Coding, called lossless-to-lossy Image Coding. In this paper, we present an efficient realization of integer fast LOT (FLOT) based on direct-lifting of discrete cosine transforms (DCTs) which are type-II, III and IV. Although the conventional integer FLOTs suffer from degradation of Coding performance due to much rounding error generated by cascading lifting structures, this paper presents a realization of a simpler, faster and more efficient transform with only some adders, 1-bit shifters and direct use of DCTs for lifting coefficients. As result, the proposed method is validated in lossless-to-lossy Image Coding.
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Integer fast lapped orthogonal transform based on direct-lifting of DCTs for lossless-to-lossy Image Coding
2011Co-Authors: Taizo SuzukiAbstract:Integer lapped orthogonal transforms (LOTs) are vital technologies for the unification of lossless and lossy Image Coding, called lossless-to-lossy Image Coding. In this paper, we present an efficient realiza-tion of integer fast LOT (FLOT) based on direct-lifting of discrete cosine transforms (DCTs) which are type-II, III and IV. Although the conventional integer FLOTs suffer from degradation of Coding per-formance due to much rounding error generated by cascading lifting structures, this paper presents a realization of a simpler, faster and more efficient transform with only some adders, 1-bit shifters and direct use of DCTs for lifting coefficients. As result, the proposed method is validated in lossless-to-lossy Image Coding. Index Terms — Direct-lifting, discrete cosine transform (DCT), fast lapped orthogonal transform (FLOT), lossless-to-lossy Image Coding 1
Takayuki Nagai - One of the best experts on this subject based on the ideXlab platform.
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generalized unequal length lapped orthogonal transform for subband Image Coding
IEEE Transactions on Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:Generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOTs) are considered. The length of each basis of the proposed GULLOT can be different from each other, whereas all the bases of the conventional GenLOT are of equal length. In general, for Image Coding application, the long basis for a low-frequency band and the short basis for a high-frequency one are desirable to reduce the blocking and the ringing artifact simultaneously. Therefore, the GULLOT is suitable especially for a subband Image Coding. In order to apply the GULLOT to a subband Image Coding, we also investigate the size-limited structure to process the finite length signal, which is important in practice. Finally, some design and Image Coding examples are shown to confirm the validity of the proposed GULLOT.
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generalized unequal length lapped orthogonal transform for subband Image Coding
International Conference on Acoustics Speech and Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:In this paper, generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOT) are considered. The length of each basis of the proposed GULLOT can be different from each other, while all the bases of the conventional GenLOT are of equal length. In order to apply the GULLOT to subband Image Coding, we also investigate the size-limited structure to process the finite length signal which is important in practice.
Masahide Kaneko - One of the best experts on this subject based on the ideXlab platform.
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generalized unequal length lapped orthogonal transform for subband Image Coding
IEEE Transactions on Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:Generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOTs) are considered. The length of each basis of the proposed GULLOT can be different from each other, whereas all the bases of the conventional GenLOT are of equal length. In general, for Image Coding application, the long basis for a low-frequency band and the short basis for a high-frequency one are desirable to reduce the blocking and the ringing artifact simultaneously. Therefore, the GULLOT is suitable especially for a subband Image Coding. In order to apply the GULLOT to a subband Image Coding, we also investigate the size-limited structure to process the finite length signal, which is important in practice. Finally, some design and Image Coding examples are shown to confirm the validity of the proposed GULLOT.
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generalized unequal length lapped orthogonal transform for subband Image Coding
International Conference on Acoustics Speech and Signal Processing, 2000Co-Authors: Takayuki Nagai, Masahide Kaneko, Akira KurematsuAbstract:In this paper, generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOT) are considered. The length of each basis of the proposed GULLOT can be different from each other, while all the bases of the conventional GenLOT are of equal length. In order to apply the GULLOT to subband Image Coding, we also investigate the size-limited structure to process the finite length signal which is important in practice.
Zixiang Xiong - One of the best experts on this subject based on the ideXlab platform.
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wavelet Image Coding using trellis coded space frequency quantization
IEEE Signal Processing Letters, 1999Co-Authors: Zixiang Xiong, Xiaolin WuAbstract:The progress in wavelet Image Coding have brought the field into its maturity. Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classification and trellis-coded quantization, and sophisticated context modeling in entropy Coding. Drawing from past experience and recent in sights, we propose a new wavelet Image Coding technique with trellis coded space-frequency quantization (TCSFQ). TCSFQ aims to explore space-frequency characterizations of wavelet Image representations via R-D optimized zerotree pruning, trellis-coded quantization, and context modeling in entropy Coding. Experiments indicate that the TCSFQ coder achieves twice as much compression as the baseline JPEG coder does at the same peak signal to noise ratio (PSNR), making it better than all other coders described in the literature.
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wavelet Image Coding using trellis coded space frequency quantization
Visual Communications and Image Processing, 1998Co-Authors: Zixiang Xiong, Xiaolin WuAbstract:Recent progresses in wavelet Image Coding have brought the field into its maturity. Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classification and trellis- coded quantization, and sophisticated context modeling in entropy Coding. Drawing from past experience and recent insight, we propose a new wavelet Image Coding technique with trellis coded space-frequency quantization (TCSFQ). TCSFQ aims to explore space-frequency characterizations of wavelet Image representations via R-D optimized zerotree pruning, trellis coded quantization, and context modeling in entropy Coding. Experiments indicate that the TCSFQ coder achieves twice as much compression as the baseline JPEG coder does at the same peak signal to noise ratio (PSNR), making it better than all other coders described in the literature.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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wavelet Image Coding using trellis coded space frequency quantization
Multimedia Signal Processing, 1998Co-Authors: Zixiang Xiong, Xiaolin WuAbstract:We propose a new wavelet Image Coding technique with trellis coded space-frequency quantization (TCSFQ). Experiments indicate that the TCSFQ coder is better than all other coders described in the literature.
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wavelet packet Image Coding using space frequency quantization
IEEE Transactions on Image Processing, 1998Co-Authors: Zixiang Xiong, Kannan Ramchandran, M T OrchardAbstract:We extend our previous work on space-frequency quantization (SFQ) for Image Coding from wavelet transforms to the more general wavelet packet transforms. The resulting wavelet packet coder offers a universal transform Coding framework within the constraints of filterbank structures by allowing joint transform and quantizer design without assuming a priori statistics of the input Image. In other words, the new coder adaptively chooses the representation to suit the Image and the quantization to suit the representation. Experimental results show that, for some Image classes, our new coder gives excellent Coding performance.
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space frequency quantization for wavelet Image Coding
IEEE Transactions on Image Processing, 1997Co-Authors: Zixiang Xiong, Kannan Ramchandran, M T OrchardAbstract:A new class of Image Coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an Image coder. We consider zerotree quantization (zeroing out tree-structured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application. We develop an Image Coding algorithm for solving the resulting optimization problem. Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates Coding performance that is competitive, often outperforming the very best Coding algorithms in the literature.
