In this paper, we proposed a bit-rate adjustable colorimage compression technique based on block truncation coding. To exploit the similarity among the neighboring pixels, the quadtree segmentation technique is used ...
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ISBN:
(纸本)9781538663509
In this paper, we proposed a bit-rate adjustable colorimage compression technique based on block truncation coding. To exploit the similarity among the neighboring pixels, the quadtree segmentation technique is used to divide the colorimage into variable-sized blocks based on their block activities. Different rules are used to encode the image blocks of different sizes. Experimental results reveal that good image qualities of the reconstructed colorimages can be achieved by the proposed technique while keeping low bit rates.
This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation,...
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This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test colorimages reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.
This paper improves a colorization-based imagecoding using image segmentation and adaptive colorspaces. Recently, various approaches for color image coding based on colorization have been presented. These methods uti...
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ISBN:
(纸本)9781509041183
This paper improves a colorization-based imagecoding using image segmentation and adaptive colorspaces. Recently, various approaches for color image coding based on colorization have been presented. These methods utilize a YCbCr colorspace and transfer the luminance component by a conventional compression method. Then, the chrominance components are approximated from the luminance component using a colorization method. Our method segments a luminance component into small segments called superpixels, and reconstructs the chrominance of each superpixel as a linear combination of its luminance. For chrominance components, we introduce an adaptive color space transform optimized for liner combination. This is because YCbCr colorspace cannot always become a good approximation of the chrominance. In addition, we introduce an automatic selection for the number of superpixel segments from a given quality factor. The simulation with standard images shows that our method performs better result than conventional coding schemes.
Two color image coding schemes based on single bit map block truncation coding are proposed in this paper. The first scheme employs the optimal rule for single bit map generation. In addition, the quantization level r...
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Two color image coding schemes based on single bit map block truncation coding are proposed in this paper. The first scheme employs the optimal rule for single bit map generation. In addition, the quantization level recomputation process is designed. By using these two techniques, a fixed bit rate imagecoding scheme is introduced. To further cut down the required bit rates of the first scheme, the similar block prediction technique and the bit map omission technique are employed in the second scheme. According to the experimental results, the first scheme proposed significantly improves the image qualities of the compressed images compared to the traditional single bit map block truncation coding scheme. In addition, good image qualities of the compressed images are achieved by the second scheme while keeping bit rates low. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
In this paper, we introduce a novel framework for lossless/near-lossless (LS/NLS) color image coding assisted by an inverse demosaicing. Conventional frameworks are typically based on prediction (and quantization for ...
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ISBN:
(纸本)9781479928941
In this paper, we introduce a novel framework for lossless/near-lossless (LS/NLS) color image coding assisted by an inverse demosaicing. Conventional frameworks are typically based on prediction (and quantization for NLS coding) followed by entropy coding, such as the JPEG-LS for bit rate saving. The approach of this work is totally different from the conventional ones. Basically, colorimages are created by demosaicing Bayer-pattern color filter array (CFA) whose operator can be expressed as square matrices. By using the (pseudo) inverse matrix of a joint demosaicing and color-to-gray conversion, the proposed decoder can recover the colorimage from its corresponding gray image data which is losslessly transmitted by the proposed encoder. Thus, LS/NLS colorimage reconstruction can be achieved while saving a bit rate significantly. In addition, using the same framework of color image coding, LS/NLS CFA coding can be realized by a comparable bit rate with JPEG-LS.
color image coding by inverse demosaicing, which exploits the implicit Bayer structure in colorimages, has a potential to achieve superior performance compared to conventional color image coding methods. The previous...
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ISBN:
(纸本)9781479983391
color image coding by inverse demosaicing, which exploits the implicit Bayer structure in colorimages, has a potential to achieve superior performance compared to conventional color image coding methods. The previous framework of inverse demosaicing was limited to lossless and near-lossless data compression, while this paper explores its adaptation to lossy compression. To cope with distortions due to lossy compression, we propose a regularization approach using side color information for the Bayer recovery problem in the decoder. Thanks to careful design of the regularization, the resulting Bayer recovery problem becomes an unconstrained quadratic programming problem, and thus several efficient solvers can be used. A numerical example demonstrates the efficacy of our approach. It can significantly reduce distortions in the recovery of the Bayer data and keep the total bit rate.
In this paper we present a new algorithm for chroma prediction in YUV images, based on inter component correlation. Despite the YUV color space transformation for inter component decorrelation, some dependency still e...
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ISBN:
(纸本)9781424479948
In this paper we present a new algorithm for chroma prediction in YUV images, based on inter component correlation. Despite the YUV color space transformation for inter component decorrelation, some dependency still exists between the Y, U and V chroma components. This dependency has been previously used to predict the chrominance data from the reconstructed luminance. In this paper we show that a chrominance component can be more efficiently predicted by using the reconstructed data from both the luminance and the remaining chrominance signal. The proposed chroma prediction is implemented and tested using the Multidimensional Multiscale Parser (MMP) image encoding algorithm. It is shown that the new color prediction mode outperforms the originally proposed prediction methods. Furthermore, by using the new color prediction scheme, MMP is consistently better than the state-of-the-art H.264/AVC for coding both for the luminance and the chrominance image components.
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.
This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conver...
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ISBN:
(纸本)9781628415001
This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level. Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V).(2) In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries(3) and thus neighboring blocks are unavailable during intra-prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low-complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.
A new way of reordering spatial orientation tree of SPIHT for improving compression efficiencies for monochrome and colorimages has been proposed. Reordering ensures that SPIHT algorithm codes more significant inform...
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A new way of reordering spatial orientation tree of SPIHT for improving compression efficiencies for monochrome and colorimages has been proposed. Reordering ensures that SPIHT algorithm codes more significant information in the initial bits. List of insignificant pixels and sets are initialized with fewer number of coefficients compared to conventional SPIHT for monochrome images. For colorimages an altered parent offspring relationship and an extra level of wavelet decomposition on chrominance planes were performed. PSNR improvement of 32.06% was achieved at 0.01 bpp for monochrome images and 19.76% for colorimages at 0.05 bpp compared to conventional schemes. (C) The Authors. Published by Elsevier B.V.
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