Combining modulation diversity and index assignment to improve image VQ for a rayleigh fading channel (original) (raw)
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Anais do XVIII Simpósio Brasileiro de Telecomunicações
A serious problem related to the transmission of vectorquantized images through noisy channels is that whenever errors occur, the nearest neighbor rule is broken. As a consequence, very annoying blocking e ects may appear in the reconstructed images. In the present work, a simple and fast method for organizing the vector quantization (VQ) codebooks is presented. The key idea behind the proposed method is to ensure that similar (dissimilar) binary representations of the indexes of the codevectors correspond to similar (dissimilar) codevectors themselves. It is shown that the organized codebooks improve the performance of the transmission system in the sense that they lead to reconstructed images with better quality when compared to the ones obtained by using non-organized codebooks.
Signal Processing, 2004
In this paper, new vector quantization (VQ) based techniques for reducing the effect of channel noise in image transmission are introduced. In one of the proposed methods, i.e., component VQ (CVQ), by transmitting the components of code-vectors (and not their indices), we will be able to reduce the effect of channel noise. To decrease the output rate of CVQ, a modification of CVQ called sub-index VQ (SIVQ) is introduced. This method has errorcorrecting capability as well. Simulation results show that CVQ and SIVQ techniques are robust to channel errors and surpass the conventional method, in which the indices of the selected code-vectors are protected using a Reed-Solomon code. An error concealment technique called shifted block concealment (SBC) has been also introduced. The stationarity assumption of small blocks of images has been utilized to conceal losses in this method.
Combined video coding and multilevel modulation
Proceedings of 3rd IEEE International Conference on Image Processing, 1996
A video transmission system based on combined source coding and multilevel modulation is proposed. For the proposed system, graceful degradation for noisy channels is obtained by nding good index maps between the quantized source coder parameters and the amplitude levels of a multilevel QAM signal constellation. The index maps are designed both for good neighbor properties and for power e cient transmission by using simulated annealing. The performance of the proposed system is comparable to a reference system based on the H.263 coder for high CSNR values, and degrades far more gracefully for low CSNR values.
Rotated constellations for video transmission over rayleigh fading channels
A joint source-channel coding scheme for transmission of video over flat Rayleigh fading channels is described. The coding scheme consists of a spatiotemporal motion-compensated wavelet decomposition, a vector quantization of the coefficients through maximum-diversity lattices, and a linear labeling which minimizes simultaneously the source and channel distortion. Modulation diversity via rotated constellations produces the maximum-diversity lattices which increase robustness to channel fading without the addition of redundancy. Experimental results compare the proposed system to a prominent scalable video coder protected by more traditional convolutional codes, and superior performance is observed for high levels of channel noise.
A fast index assignment method for robust vector quantisation of image data
Vector quantisation is a widely used technique in low-bit rate coding of speech and image data, but is highly sensitive to noise in the transmission channel. If the reference vector recalled by a corrupted index diers greatly from the intended reference vector, image quality can be degraded quite dramatically. The index assignment (IA) process attempts to reorder the code book so as to minimise the eects of errors introduced in the transmission channel, by assigning indices with similar binary patterns to similar reference v e ctors, usually at considerable computational expense. This paper describes a fast, novel index assignment algorithm based on Hall's solution to the quadratic assignment problem [6].
Markov system for image vector quantization coding
Optical Engineering, 2000
Vector quantization (VQ) has been accepted as one of the most effective image compression methods with provable rate-distortion optimality. The outputs of VQ are a collection of indices, which correspond to the addresses of the codevectors in the codebook. The indices are, however, not mutually independent. They are in fact very highly correlated and are thus appropriately described by a Markov system. In this paper, a Markov system for VQ indices is introduced. Statistics are gathered for various scans, such as the zigzag , Peano, row-major and column-major scans. The proposed method, like address VQ, achieves the same image quality as conventional VQ. Simulation results show that the proposed method achieves a better bit-rate reduction than Address-VQ. Besides, both the computational complexity and memory needed for the proposed method are lower. Nevertheless, the only extra operation needed by the proposed method is a simple table retrieval operation on both the encoder side and the decoder side. We believe that it is a method worth further exploration.
Index compressed image adaptive vector quantisation
Signal Processing-image Communication, 1996
This paper introduces an improved image adaptive vector quantisation technique-index compressed image adaptive vector quantisation (IC-IAVQ). Despite its advantage over the universal codebook VQ, basic image adaptive VQ (IAVQ) is still suboptimum; it neglects the correlation among block indices in the encoded image. The new technique, IC-IAVQ, overcomes this suboptimality through a pre-processing and lossless compression of block indices. Simulation results using several images show that IC-IAVQ outperforms IAVQ and entropy coded IAVQ, especially at low bit-rates by about 2dB on average.
Image Vector Quantization codec indexes filtering
Serbian Journal of Electrical Engineering, 2012
Vector Quantisation (VQ) is an efficient coding algorithm that has been widely used in the field of video and image coding, due to its fast decoding efficiency. However, the indexes of VQ are sometimes lost because of signal interference during the transmission. In this paper, we propose an efficient estimation method to conceal and recover the lost indexes on the decoder side, to avoid re-transmitting the whole image again. If the image or video has the limitation of a period of validity, re-transmitting the data wastes the resources of time and network bandwidth. Therefore, using the originally received correct data to estimate and recover the lost data is efficient in time-constrained situations, such as network conferencing or mobile transmissions. In nature images, the pixels are correlated with their neighbours and VQ partitions the image into sub-blocks and quantises them to the indexes that are transmitted; the correlation between adjacent indexes is very strong. There are two parts of the proposed method. The first is pre-processing and the second is an estimation process. In pre-processing, we modify the order of codevectors in the VQ codebook to increase the correlation among the neighbouring vectors. We then use a special filtering method in the estimation process. Using conventional VQ to compress the Lena image and transmit it without any loss of index can achieve a PSNR of 30.429 dB on the decoder. The simulation results demonstrate that our method can estimate the indexes to achieve PSNR values of 29.084 and 28.327 dB when the loss rate is 0.5% and 1%, respectively.
Fast index assignment algorithm for vector quantisation over noisy transmission channels
1996
Abstract Vector quantisation, a widely used technique in low bit rate coding of speech signals, is highly sensitive to errors in the transmitted codeword caused by noise in the transmission channel. The authors describe an efficient index assignment algorithm, based on Hall's solution to the quadratic assignment problem, used to re-order the codebook such that the effect of transmission errors is minimised