The Noise Reduction over Wireless Channel Using Vector Quantization Compression and Filtering

The transmission of compressed data over wireless channel conditions represents a big challenge. The idea of providing robust transmission gets a lot of attention in field of research. In this paper we study the effect of the noise over wireless channel. We use the model of Gilbert-Elliot to represent the channel. The parameters of the model are selected to represent three cases of channel. As data for transmission we use images in gray level size 512x512. To minimize bandwidth usage we compressed the image with vector quantization also in this compression technique we study the effect of the codebook in the robustness of transmission so we use different algorithms to generate the codebook for the vector quantization finally we study the restoration efficiency of received image using filtering and indices recovery technique

Interleaved reception method for restored vector quantization image

The transmission of image compression by vector quantization produce wrong blocks in received image which are completely different to the original one that makes the restoration process too hard because we don’t have any information about the original blocks. As a solution of this problem we try to keep the maximum of pixels that form the original block by building new blocks. Our proposition is based on decomposition and interleaving. For the simulation we use a binary symmetric channel with different BER and in the restoration process we use simple median filter just to check the efficiency of proposed approach

Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

In this paper we are going to study the effect of channel noise in image compressed with vector quantization and discrete wavelet transform. The objective of this study is to analyze and understand the way that the noise attack transmitted data by doing lot of tests like dividing the indices in different levels according to discrete wavelet transform and dividing  each level in frames of bits. The collected information well helps us to propose solutions to make the received image more resistible to the channel noise also to benefit from the good representation obtained by using vector quantization and discrete wavelet transform

Improving quality of medical image compression using biorthogonal CDF wavelet based on lifting scheme and SPIHT coding

As the coming era is that of digitized medical information, an important challenge to deal with is the storage and transmission requirements of enormous data, including medical images. Compression is one of the indispensable techniques to solve this problem. In this work, we propose an algorithm for medical image compression based on a biorthogonal wavelet transform CDF 9/7 coupled with SPIHT coding algorithm, of which we applied the lifting structure to improve the drawbacks of wavelet transform. In order to enhance the compression by our algorithm, we have compared the results obtained with wavelet based filters bank. Experimental results show that the proposed algorithm is superior to traditional methods in both lossy and lossless compression for all tested images. Our algorithm provides very important PSNR and MSSIM values for MRI images

Robust image transmission performed by SPIHT and turbo-codes

This work describes the method for providing robustness to errors from a binary symmetric channel for the SPIHT image compression. The source rate and channel rate are jointly optimized by a stream of fixed-size channel packets. Punctured turbo codes are used for the channel coding, providing stronger error protection than previously available codes. We use the most appropriate set of puncturing patterns that ensure the best source rate. The presented rate allocation scheme obtains all necessary information from the SPIHT encoder, without requiring image decompression

Image Vector Quantization codec indexes filtering

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

Investigation of the performance of modified TCM scheme for the protection of SPIHT-based compressed images over fading channel

International audienceIn this paper, a new variant of trellis-coded modulation with Ungerboeck-Gray mapping 'TCM-UGM' is presented for spectral efficiency of 2 bit/s/Hz. The performance of this encoding scheme is investigated over Rayleigh fading channel. The simulation result, using 16-state TCM-UGM encoder, shows clearly that the proposed scheme outperforms the performance of the 32-state TCM by 2.8 dB at BER=10-5. Both compression and transmission errors may degrade the quality of images. To illustrate the effectiveness of the proposed system for transmission the compressed image with the CDF9/7 wavelet and SPIHT coding, a comparison between the TCM and the new variant the TCM-UGM is presented. Simulation results on several types of compressed image were presented. For this study, four Image Quality Metrics (IQMs) were employed in the image quality assessment after the transmission. Results show that the new variant of TCM-UGM reduces transmission errors and better protects the compressed image during transmission