摘要 :
In this paper, it is shown that there is useful method for improving PSNR of lossy Hadamard transform. This method cancelled mean component of the rounding errors which is generated at rounding process in transform, with offset ad...
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In this paper, it is shown that there is useful method for improving PSNR of lossy Hadamard transform. This method cancelled mean component of the rounding errors which is generated at rounding process in transform, with offset added at rounding process in inverse transform. As a result of improving PSNR of lossy Hadamard transform, partial of input data space is reversibly transformed. Input data space can be divided into two partial spaces. One is the space in which total sum of data is even. Another is the space in which total sum of data is odd. There are many vectors from which offset matrix can be generated such that one of tow partial spaces is reversibly transformed. We propose new lossless 2D-Hadamard Transform which exchanges two offset matrix based on that the sum of data is odd or even. It is shown that entropy of the lossless transformed coefficients is scarcely affected by selection of offset matrix.
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摘要 :
The lossless (reversible) discrete cosine transform (DCT) is a very useful transform because it can realize easily an unified lossy/lossless image coding with a compatibility with conventional scheme such as MPEG and MPEG But on c...
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The lossless (reversible) discrete cosine transform (DCT) is a very useful transform because it can realize easily an unified lossy/lossless image coding with a compatibility with conventional scheme such as MPEG and MPEG But on conventional transform coding based on lossless DCT, its compression performance at high-bit rate coding is poorer at high-bit rate coding and it can't ensure the quantity of the maximum error of recovered image. We propose a new transform coding based on lossless DCT in this report Proposed method can solve the problem in conventional method.
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摘要 :
The lossless (reversible) discrete cosine transform (DCT) is a very useful transform because it can realize easily an unified lossy/lossless image coding with a compatibility with conventional scheme such as MPEG and MPEG But on c...
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The lossless (reversible) discrete cosine transform (DCT) is a very useful transform because it can realize easily an unified lossy/lossless image coding with a compatibility with conventional scheme such as MPEG and MPEG But on conventional transform coding based on lossless DCT, its compression performance at high-bit rate coding is poorer at high-bit rate coding and it can't ensure the quantity of the maximum error of recovered image. We propose a new transform coding based on lossless DCT in this report Proposed method can solve the problem in conventional method.
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摘要 :
This paper suggested a new efficient lossless compression algorithm for vector maps in view of the graphical characteristics. First, we adopt the differential lossless transformation for the graphic data in the vector map files, t...
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This paper suggested a new efficient lossless compression algorithm for vector maps in view of the graphical characteristics. First, we adopt the differential lossless transformation for the graphic data in the vector map files, to make the original data which should have been represented by double model or float model be represented by long model. Then, based on the abbreviated compression, the prediction coding based on the irregular coefficients is used. Namely, it is to dynamically distribute proper byte storage to the transformed coefficients which have been differentiated according to the numerical values, and compressed further combined with a dictionary coding method. Finally, we do an experimental contrast for the compression effect.
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摘要 :
Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the los...
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Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the lossless DCT and those of the lossy (conventional) DCT is not small, when the same image is an input. Therefore, in this paper, we will design a two dimensional lossless DCT based on two dimensional 4-point lossless WHT and indicate that the number of rounding off in ladder circuit becomes smaller than that of one dimensional lossless DCTs and, therefore, the difference between transform coefficients of the two dimensional lossless DCT and those of the lossy DCT becomes small. We will also design two dimensional 8×8-point lossless WHT and indicate that the compatibility with the lossy WHT is high and that the number of multiplication is zero.
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摘要 :
Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the los...
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Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the lossless DCT and those of the lossy (conventional) DCT is not small, when the same image is an input. Therefore, in this paper, we will design a two dimensional lossless DCT based on two dimensional 4-point lossless WHT and indicate that the number of rounding off in ladder circuit becomes smaller than that of one dimensional lossless DCTs and, therefore, the difference between transform coefficients of the two dimensional lossless DCT and those of the lossy DCT becomes small. We will also design two dimensional 8×8-point lossless WHT and indicate that the compatibility with the lossy WHT is high and that the number of multiplication is zero.
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摘要 :
Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the los...
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Since the lossless DCT is compatible with JPEG or MPEG, it is expected to play an important role in the unified lossless/lossy image coding. However, there is a problem that the difference between transform coefficients of the lossless DCT and those of the lossy (conventional) DCT is not small, when the same image is an input. Therefore, in this paper, we will design a two dimensional lossless DCT based on two dimensional 4-point lossless WHT and indicate that the number of rounding off in ladder circuit becomes smaller than that of one dimensional lossless DCTs and, therefore, the difference between transform coefficients of the two dimensional lossless DCT and those of the lossy DCT becomes small. We will also design two dimensional 8×8-point lossless WHT and indicate that the compatibility with the lossy WHT is high and that the number of multiplication is zero.
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摘要 :
We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are...
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We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are used. In lossy mode, transformed coefficients of the L-DCT are quantized and then entropy coded as same as a conventional lossy method for compatibility. In this maruter, coding results are almost similar to these of the conventional lossy method except high bit rate because of rounding operation in the L-DCT Therefore, in near-lossless mode, we put quantization before the L-DCT to avoid the rounding effect. The tuning point between near-lossless mode and lossy mode is also theoretically analyzed. Simulation results cortf'trm effectiveness of our integrated system.
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摘要 :
We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are...
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We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are used. In lossy mode, transformed coefficients of the L-DCT are quantized and then entropy coded as same as a conventional lossy method for compatibility. In this maruter, coding results are almost similar to these of the conventional lossy method except high bit rate because of rounding operation in the L-DCT Therefore, in near-lossless mode, we put quantization before the L-DCT to avoid the rounding effect. The tuning point between near-lossless mode and lossy mode is also theoretically analyzed. Simulation results cortf'trm effectiveness of our integrated system.
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摘要 :
We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are...
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We propose a new coding method integrating 3 coding modes - lossless, near-lossless and 1ossy coding modes - under a unified single algorithm based on lossless DCT (L-DCT). In lossless mode, only the L-DCT and an entropy coder are used. In lossy mode, transformed coefficients of the L-DCT are quantized and then entropy coded as same as a conventional lossy method for compatibility. In this maruter, coding results are almost similar to these of the conventional lossy method except high bit rate because of rounding operation in the L-DCT Therefore, in near-lossless mode, we put quantization before the L-DCT to avoid the rounding effect. The tuning point between near-lossless mode and lossy mode is also theoretically analyzed. Simulation results cortf'trm effectiveness of our integrated system.
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