In this paper, a new algorithm for progressive medical imagecoding is presented. An 8-bit gray scale image is divided into eight binary bit-planes, and then, binary wavelet transform is performed on each bit-plane to...
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In this paper, a new algorithm for progressive medical imagecoding is presented. An 8-bit gray scale image is divided into eight binary bit-planes, and then, binary wavelet transform is performed on each bit-plane to extract the three-level multi-resolution binary wavelet transformed images. Starting from the most significant bit-plane, each bit-plane is encoded using quadtree-based partitioning scheme to exploit the energy concentration in the high-frequency subbands. Experiments are conducted on ultrasound, MRI and CT images to prove the effectiveness of the proposed algorithm. The results show a significant improvement in terms of bit-rate for the required peak signal-to-noise ratio and correlation coefficient as compared to the existing state-of-art progressive image coding methods.
Set partitioning in hierarchical trees (SPIHT) has become a popular research topic for more than a decade now. This is because it is simple, besides having compression efficiency close to the state-of-the-art JPEG2000...
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Set partitioning in hierarchical trees (SPIHT) has become a popular research topic for more than a decade now. This is because it is simple, besides having compression efficiency close to the state-of-the-art JPEG2000 standard. The main drawback of SPIHT is that it uses three lists to store addresses of coefficients during its operation. These lists are dynamic and in worst cases need to store more number of addresses than total coefficients. In this work, a novel hardware-efficient spatial orientation tree-based algorithm is proposed and its hardware implementation is carried out. The wavelet transformed image is partitioned into 2 x 2 blocks. Each node of spatial orientation tree (SOT) represent a block of coefficients, rather than a single coefficient. Two small state-tables are used in this algorithm to store the status of each block. In addition to this, two extremely small lists are used to store the node addresses of a single SOT tree. To store the state-tables and lists for 512 x 512 image, only 0.88% of the memory needed by SPIHT is required for five levels of dyadic decomposition. The peak-signal-to-noise ratio (PSNR) gain of 0.1 dB to 0.3 dB at low bit rates (below 1 bpp) and 0.6 dB to 1.2 dB at high bit rates (above 1.75 bpp) in comparison to SPIHT is observed for test image Lena. A field programmable gate array (FPGA) implementation targeted for Xilinx Zynq Z-7020 is presented in the paper. The proposed architecture saves 90% of the FPGA area used by SPIHT. The hardware efficiency of the proposed architecture is better in comparison to different existing architectures.
In Internet applications, compressing the image without perceptually distinguishable distortions and loading the images without notable delays in the client end can significantly improve the user experience. Compressi...
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ISBN:
(纸本)9781728147048
In Internet applications, compressing the image without perceptually distinguishable distortions and loading the images without notable delays in the client end can significantly improve the user experience. Compressing the image at high bit rates can maintain the high quality of the decoded image but in cost of long transmitting and decoding time, resulting in bad user experience. The progressivecoding scheme can resolve the conflict between the high quality requirement and the large loading delay. This paper proposes a novel efficient progressive image coding framework based on deep convolutional neural networks. The proposed framework is composed of a uniform encoder network and two progressive decoder networks. The encoder network decomposes the input image into two scales of representations, that can be transmitted and reconstructed progressively into a basic quality preview image and a high-quality image by two individual decoder networks respectively. All the networks are jointly learned when achieving the rate distortion optimization of both scales. Experiments results show that the proposed method has much better coding performance than the commercial codecs WebP and JPEG, which are commonly used in Internet applications. Meanwhile, the proposed codec consumes much less time to load the image compared with WebP.
In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multi resolutio...
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ISBN:
(纸本)9781479954865
In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multi resolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead Bandlet transform is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the Bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.
We propose a fast trellis-based rate-allocation algorithm for robust transmission of progressively coded images over noisy channels. The algorithm, which is an improved version of a similar algorithm by Banister et al...
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We propose a fast trellis-based rate-allocation algorithm for robust transmission of progressively coded images over noisy channels. The algorithm, which is an improved version of a similar algorithm by Banister et al., is based on the application of the Viterbi algorithm to a search trellis. This trellis is a substantially trimmed version of the one used by Banister et al.. The proposed algorithm is applied to images encoded by the set partitioning in hierarchical trees and the Joint Photographers Expert Group 2000 for transmission over binary symmetric channels. For different total bit budgets and channel parameters, speed-up factors of up to about three orders of magnitude are achieved.
A two-stage lossless compression method based on a binary tree representation of colors and on context-based arithmetic coding has been recently proposed. We propose two improvements to this method: merge-based color ...
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ISBN:
(纸本)9781424404810
A two-stage lossless compression method based on a binary tree representation of colors and on context-based arithmetic coding has been recently proposed. We propose two improvements to this method: merge-based color quantization instead of the original splitting strategy, and context tree modeling optimized for each layer separately. The proposed method achieves better compression performance, and a better reproduction quality in the color progression.
This paper addresses progressive wavelet imagecoding within the trellis-coded space-frequency quantization (TCSFQ) framework [1]. A method similar to that in[2] is used to approximately invert TCSFQ when decoding at ...
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ISBN:
(纸本)0819440833
This paper addresses progressive wavelet imagecoding within the trellis-coded space-frequency quantization (TCSFQ) framework [1]. A method similar to that in[2] is used to approximately invert TCSFQ when decoding at rates lower than the encoding rate. Our experiments show that the loss incurred for progressive transmission is within one dB in PSNR and that the progressivecoding performance of TCSFQ is competitive with that of the celebrated SPIHT coder [3] at all rates.
One main focus of research in stereo imagecoding has been disparity estimation, a technique used to reduce the coding rate by taking advantage of the redundancy in a stereo image pair. Significantly less effort has b...
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One main focus of research in stereo imagecoding has been disparity estimation, a technique used to reduce the coding rate by taking advantage of the redundancy in a stereo image pair. Significantly less effort has been put into the coding of the residual image. These images display characteristics that are different from that of natural images. We propose a new method for the coding of residual images that takes into account the properties of residual images. Particular attention is paid to the effects of occlusion and the correlation properties of residual images that result from block-based disparity estimation. The embedded, progressive nature of our coder enables one to stop decoding at any time. We demonstrate that it is possible to achieve good results with a computationally simple method. (C) 2003 Society of Photo-Optical Instrumentation Engineers.
This paper addresses progressive wavelet imagecoding within the trellis-coded space-frequency quantization (TCSFQ) framework [1]. A method similar to that in [2] is used to approximately invert TCSFQ when decoding at...
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This paper addresses progressive wavelet imagecoding within the trellis-coded space-frequency quantization (TCSFQ) framework [1]. A method similar to that in [2] is used to approximately invert TCSFQ when decoding at rates lower than the encoding rate. Our experiments show that the loss incurred for progressive transmission is within I dB in peak signal-to-noise ratio and that the progressivecoding performance of TCSFQ is competitive with that of the celebrated SPIHT coder [3] at all rates.
Remote Sensing and Geographic Information Systems applications are becoming more and more present in everyday life. These applications are based on the owing availability of natural, multi-spectral and hyper-spectral ...
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ISBN:
(纸本)0819450235
Remote Sensing and Geographic Information Systems applications are becoming more and more present in everyday life. These applications are based on the owing availability of natural, multi-spectral and hyper-spectral images, but these kind of images imposes a large demand of memory capability due to their large size and increasing resolution. Well known lossless and lossy imagecoding techniques have been used to settle down this problem, but RS and GIS applications have some particular requirements that are not taken into account by the standard methods. There is therefore a need to investigate new approaches of imagecoding for RS and GIS applications.
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