文件名称:TURBOCODEAPPTOIMAGETRANSMISSION
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- 上传时间:2012-11-16
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Simulations over AWGN and Rayleigh channels, at various signal-to-noise ratios, verify the excellent performance of this novel APEL-turbo scheme. Performance comparisons were carried out between turbo coded APEL, JPEG, and BMP image files.
To provide a fair comparison between the APEL and JPEG images, compression level had to be the same. This resulted in the data reduction for both APEL and JPEG to be around 5 to 1.
In the assessment of bit errors within a received image file, a quantitative pixel error rate offers a fairer comparison. Therefore, it is appropriate to represent the error performance in a ratio called “Pixel Error Rate (PER)”, which is a measure of the degree of image degradation.
Through the analysis of the ith received pixel’s variance from its transmitted value, a measure of visual disturbance, Δi, can be quantified as in (1), where ti and ri represent the transmitted and received pixel colours respectively, for an n colour image.
To provide a fair comparison between the APEL and JPEG images, compression level had to be the same. This resulted in the data reduction for both APEL and JPEG to be around 5 to 1.
In the assessment of bit errors within a received image file, a quantitative pixel error rate offers a fairer comparison. Therefore, it is appropriate to represent the error performance in a ratio called “Pixel Error Rate (PER)”, which is a measure of the degree of image degradation.
Through the analysis of the ith received pixel’s variance from its transmitted value, a measure of visual disturbance, Δi, can be quantified as in (1), where ti and ri represent the transmitted and received pixel colours respectively, for an n colour image.
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TURBO CODE APPLICATION TO IMAGE TRANSMISSION.pdf
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