This paper presents a new method for coding the chromatic component of a colorimage that exploits the piecewise-constant nature of chromatic information. The image is first transformed to a color space in which chrom...
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ISBN:
(纸本)0819427497
This paper presents a new method for coding the chromatic component of a colorimage that exploits the piecewise-constant nature of chromatic information. The image is first transformed to a color space in which chromatic information is nearly piecewise constant. The chromatic component is then represented by entries from a codebook of two-dimensional chromatic vectors adapted to the given image (two-dimensional vector quantization). Both memoryless quantization and quantization with spatial memory are considered. Finally, the field of labels is coded using a suitable lossless code with memory. we have used a context-dependent arithmetic code. Experimental results showing rate-distortion performance of-the method under various conditions are presented.
Digital image representation is perceptually uniform if a small perturbation of a component valuesuch as the digital code value used to represent red, green, blue, or luminanceproduces a change in light output at a di...
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Digital image representation is perceptually uniform if a small perturbation of a component valuesuch as the digital code value used to represent red, green, blue, or luminanceproduces a change in light output at a display that is approximately equally perceptible across the range of that value. Most digital imagecoding systemsincluding sRGB (used in desktop graphics), BT.709 (used in high-definition television, HD), Adobe RGB (1998) (used in graphics arts), and DCI P3 RGB (used in digital cinema)represent colour component (pixel) values in a perceptually uniform manner. However, this behavior is not well documented and is often shrouded in confusion. This article surveys perceptual uniformity in digital imaging and attempts to clarify some widely misunderstood aspects of imagecoding. (c) 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 6-15, 2014
This paper presents an image adaptive linear filtering method for the reconstruction of the RGB (red, blue, green) color coordinates of a pixel from the lossy compressed luminance/chrominance color coordinates. In the...
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This paper presents an image adaptive linear filtering method for the reconstruction of the RGB (red, blue, green) color coordinates of a pixel from the lossy compressed luminance/chrominance color coordinates. In the absence of quantization noise, the RGB coordinates of a pixel can be perfectly reconstructed by employing a standard, fixed filter whose support includes only the luminance/chrominance coordinates at the spatial location of the pixel. However, in the presence of quantization noise, a filter with a larger support, that also spatially extends over the luminance/chrominance coordinate planes, is capable of exploiting the statistical dependence among the luminance/chrominance coordinate planes, and thereby yields more accurate reconstruction than the standard, fixed filter. We propose the optimal (in the minimum mean squared error sense) determination of the coefficients of this adaptive linear filter at the image encoder by solving a system of regression equations. When transmitted as side information to the image decoder, the filter coefficients need not incur significant overhead if they are quantized and compressed intelligently. Our simulation results demonstrate that the distortion of the decompressed color coordinate planes can be reduced by several tenths of a dB with negligible overhead rate by the application of our image adaptive linear filtering method. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper, a new multi stage vector quantization with energy clustered training set is proposed for color image coding. The input image is applied with orthogonal polynomials based transformation and the energy cl...
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In this paper, a new multi stage vector quantization with energy clustered training set is proposed for color image coding. The input image is applied with orthogonal polynomials based transformation and the energy clustered transformed training vectors are obtained with reduced dimension. The stage-by-stage codebook for vector quantization is constructed from the proposed transformed training vectors so as to reduce computational complexity. This method also generates a single codebook for all the three color components, utilizing the inter-correlation property of individual color planes and interactions among the color planes due to the proposed transformation. As a result, the colorimage encoding time is only slightly higher than that of gray scale imagecoding time and in contrast to the existing color image coding techniques, whose time is thrice greater than that of gray scale imagecoding. The experimental results reveal that only 35 % and 10 % of transform coefficients are sufficient for smaller and larger blocks respectively, for the reconstruction of images with good quality. The proposed multi stage vector quantization technique is faster when compared to existing techniques and yields better trade-off between image quality and block size for encoding.
In this paper we analyze the impact of tree structures on the performance of zerotree-based wavelet video codecs. Since zerotree approach is based on aggregation of insignificant coefficients in trees, therefore desig...
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In this paper we analyze the impact of tree structures on the performance of zerotree-based wavelet video codecs. Since zerotree approach is based on aggregation of insignificant coefficients in trees, therefore design of a tree structure is the key issue for a better performance. We have considered six different tree structures with characteristics varying from a simple to relatively complex and composite tree structures to code the luminance-chrominance components of a video sequence. Their performances are compared in terms of average number of bits generated per bitplane, number of coded bitplanes for a given bit budget, rate-distortion performance, memory requirements and computational complexity. We observe that in general more complex and longer trees do not necessarily improve the coding efficiency. However, the tree structures encapsulating more elements per tree are memory efficient. Therefore, the rate-distortion performance, memory requirements and computational complexities need to be traded-off while selecting a particular tree structure. It is also observed that the additional improvement due to optional entropy coding is also tree structure dependent. Further, the simulation results show that by designing an efficient tree structure, depending on the picture content, the performance of a video coder can be improved by up to 2.0 dB, while reducing the computational complexity by 45-60% as well as the memory requirements by almost 29-35%. Compared to the standard JPEG2000 (for intra-frame), tree-based coders are found to be efficient in terms of coding and complexity, particularly at lower bit rates. (C) 2010 Elsevier B.V. All rights reserved.
JPEG 2000 is a new imagecoding system that delivers superior compression performance and provides many advanced features in scalability, flexibility, and system functionalities that outperform all previous standards....
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JPEG 2000 is a new imagecoding system that delivers superior compression performance and provides many advanced features in scalability, flexibility, and system functionalities that outperform all previous standards. It brings exciting possibilities to many imaging applications such as the Internet, wireless, security, and digital cinema. This paper gives an overview of this triumph in innovations and teamwork. It gives brief introductions to the four new parts that are under development by the JPEG committee. It attempts to summarize the lessons learned from the JPEG 2000 development experience and draw some conclusions on the success factors of this important standard.
In general, to achieve high compression efficiency, a 2D image or a 2D block is used as the compression unit. However, 2D compression requires a large memory size and long latency when input data are received in a ras...
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In general, to achieve high compression efficiency, a 2D image or a 2D block is used as the compression unit. However, 2D compression requires a large memory size and long latency when input data are received in a raster scan order that is common in existing TV systems. To address this problem, a 1D compression algorithm that uses a 1D block as the compression unit is proposed. 1D set partitioning in hierarchical trees (SPIHT) is an effective compression algorithm that fits the encoded bit length to the target bit length precisely. However, the 1D SPIHT can have low compression efficiency because 1D discrete wavelet transform (DWT) cannot make use of the redundancy in the vertical direction. This paper proposes two schemes for improving compression efficiency in the 1D SPIHT. First, a hybrid coding scheme that uses different coding algorithms for the low and high frequency bands is proposed. For the low-pass band, a differential pulse code modulation-variable length coding (DPCM-VLC) is adopted, whereas a 1D SPIHT is used for the high-pass band. Second, a scheme that determines the target bit length of each block by using spatial correlation with a minimal increase in complexity is proposed. Experimental results show that the proposed algorithm improves the average peak signal to noise ratio (PSNR) by 2.97 dB compared with the conventional 1D SPIHT algorithm. With the hardware implementation, the throughputs of both encoder and decoder designs are 6.15 Gbps, and gate counts of encoder and decoder designs are 42.8 K and 57.7 K, respectively. (C) 2015 Elsevier B.V. All rights reserved.
Based on the idea of second generation imagecoding, a novel scheme for coding still images is pre- *** first, an image was partitioned with a pulse-coupled neural network; and then an improved chain code and the 2D d...
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Based on the idea of second generation imagecoding, a novel scheme for coding still images is pre- *** first, an image was partitioned with a pulse-coupled neural network; and then an improved chain code and the 2D discrete cosine transform was adopted to encode the shape and the color of its edges *** code its smooth and texture regions, an improved zero-trees strategy based on the 2nd generation wavelet was *** that, the zero-tree chart was selected to rearrange quantified *** finally some regulations were given according to psychology of various *** under noiseless channels demonstrate that the proposed method performs better than those of the current one, such as JPEG, CMP, EZW and JPEG2000.
Mean squared error (MSE), or its equivalence, peak signal-to-noise ratio (PSNR), has been widely used as the quality metric in image compression for long time. Meanwhile, numerous evidences testified the loose correla...
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ISBN:
(纸本)9780889865839
Mean squared error (MSE), or its equivalence, peak signal-to-noise ratio (PSNR), has been widely used as the quality metric in image compression for long time. Meanwhile, numerous evidences testified the loose correlation between MSE (or PSNR) and the subjective quality assessment result of the same distorted image. If MSE is such an unreliable quality metric, why do encoders based on it work well in most cases? But if it works well in image compression, why can't people count on it in objective quality assessment? These questions are investigated in this paper under the framework of JPEG baseline compression on colorimages. We concluded that MSE generally works well in comparing two images compressed by the same encoder, since they normally share the same distortion structure. When comparing compressed images from different encoders or artificially distorted images. MSE will perform very poor, since there are significant discrepancies between the essence of MSE and contrast sensitivities of human visual system.
In this paper, a low memory strip-based image compression for colorimages using the set-partitioning in hierarchical trees (SPIHT) coding is presented. The proposed coding scheme applies a lower scale of discrete wav...
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ISBN:
(纸本)9780769537528
In this paper, a low memory strip-based image compression for colorimages using the set-partitioning in hierarchical trees (SPIHT) coding is presented. The proposed coding scheme applies a lower scale of discrete wavelet decomposition and uses a new spatial orientation tree structure to achieve a low memory strip-based coding implementation. It also incorporates a modified SPIHT algorithm which uses a degree-0 to degree-2 zerotree coding methodology to increase the compression efficiency. The main advantage of the proposed work is the significant reduction in both the memory requirements as well as the complexity of the image coder for practical software and hardware implementation. Simulation results on colorimages also show that the proposed coding scheme gives a better compression performance compared to the traditional SPIHT coding at most bit-rates.
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