An Adaptive Source-Channel Coding with Feedback for Progressive Transmission of Medical Images

Lo, Jen-Lung; Sanei, Saeid; Nazarpour, Kianoush

doi:10.1155/2009/519417

Cited by 6 publications

(5 citation statements)

References 23 publications

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“…where, X m = Mean of the input image Y m = Mean of the output image PSNR Based on mean squared errors (MSE), PSNR is defined as PSNR = 10 log 10 (L-1) 2 / MSE (11) Note that, greater the PSNR, the better the output. Standard Deviation By measuring the standard deviation, we can get the contrast of the image.…”

Section: Ambementioning

confidence: 99%

Enhanced image transmission with error control

Jagatheeswari¹,

Rajaram²

2011

2011 International Conference on Emerging Trends in Electrical and Computer Technology

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Contrast enhancement of an image can efficiently performed by Histogram Equalization. However, this method tends to introduce unnecessary visual deterioration such as saturation effect. One of the solutions to overcome this weakness is by preserving the mean brightness of the input image inside the output image. This paper proposes a new histogram equalization method called Contrast Stretching Recursively Separated Histogram Equalization (CSRSHE), for brightness preservation and image contrast enhancement. After that a channel coding scheme for progressive transmission of enhanced images is proposed. The transmission time, low distortion reconstructed image and low complexity are most concerned in this paper. The progressive transmission is based on the process that the input image is decomposed into many subblocks each to be coded, compressed, and transmitted individually. In the proposed system, we choose a 3-level Haar wavelet transform to perform the wavelet transform for each subblock. It is simple, faster and easier to implement when compared with other transform method. The channel coding used here is Hamming code which is a simpler and efficient forward error control code. Also we show that compared to other existent methods, our proposed enhanced method (CSRSHE) preserves the image brightness more accurately and produces images with better contrast enhancement.

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Section: Ambementioning

confidence: 99%

Enhanced image transmission with error control

Jagatheeswari¹,

Rajaram²

2011

2011 International Conference on Emerging Trends in Electrical and Computer Technology

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“…In fact, an arbitrary polynomial of degree less than n is a codeword polynomial if and only if it satisfies equation (4). A systematic encoding produces codeword polynomials that are comprised of data followed by parity check symbols , and it is obtained as follows (5).…”

Section: ) Reed-solomon Encodingmentioning

confidence: 99%

“…In [4], the authors have presented a new adaptive sourcechannel coding with feedback for the progressive transmission of medical images. The system is adaptive to both image content and channel specifications.…”

Section: Introductionmentioning

confidence: 99%

Image transmission quality analysis over adaptive Reed-Solomon coding

Fourati

Kamoun

2010

Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference

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Image compression standard are sensitive to channel noise, so for noisy channels it is necessary to investigate in order to select the appropriate channel coding method as a trade-off between the image quality and the ability to control errors. ReedSolomon (RS) codes which are described by Reed and Solomon in 1960[1] are powerful error correcting codes and are becoming more frequently used due to the availability of VLSI components. RS codes have a powerful random and burst correcting ability. The Reed-Solomon code can be adapted towards the burst error correcting capabilities and this will be shown in the contribution. This paper investigates the effects of noise on the performance of Reed-Solomon coding methods for different errors correction capability. First, the relations among the BER, SNR, and code lengths are analysed. Further, the transmission performance of RS codes association with different modem schemes are analysed. The results listed in this article denote the effects of the using RS codes in a selected method. Based on this analysis an adaptive RS scheme is proposed to decide on the correcting capabilities that offers the best reconstructed image quality.

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“…In a more general framework, such as 2-D medical image transmission over error-prone channels, important source coding methods that incorporate channel coding have been reported [15], [16]. In [15], the authors present a JSCC method for transmission over the Internet protocol.…”

Section: Introductionmentioning

confidence: 99%

“…LAR compression is employed to achieve scalability, while the Mojette transform is employed to build an UEP system that assigns protection according to the error sensitivity of the Mojette-transformed data and the network packet-loss rate. In [16], the authors present a JSCC method based on the wavelet transform, embedded zerotree wavelet coding and Reed-Solomon codes. The method allows for the definition of a RoI and assigns UEP to different areas of the image according to their radial proximity to the RoI.…”

Section: Introductionmentioning

confidence: 99%

Joint Source/Channel Coding for Prioritized Wireless Transmission of Multiple 3-D Regions of Interest in 3-D Medical Imaging Data

Sánchez

2013

IEEE Trans. Biomed. Eng.

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This paper presents a 3-D medical image coding method featuring two major improvements to previous work on 3-D region of interest (RoI) coding for telemedicine applications. Namely, 1) a data prioritization scheme that allows coding of multiple 3-D-RoIs; and 2) a joint/source channel coding scheme that allows prioritized transmission of multiple 3-D-RoIs over wireless channels. The method, which is based on the 3-D integer wavelet transform and embedded block coding with optimized truncation with 3-D context modeling, generates scalable and error-resilient bit streams with 3-D-RoI decoding capabilities. Coding of multiple 3-D-RoIs is attained by prioritizing the wavelet-transformed data according to a Gaussian mixed distribution, whereas error resiliency is attained by employing the error correction capabilities of rate-compatible punctured turbo codes. The robustness of the proposed method is evaluated for transmission of real 3-D medical images over Rayleigh-fading channels with a priori knowledge of the channel condition. Evaluation results show that the proposed coding method provides a superior performance compared to equal error protection and unequal error protection techniques.

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An Adaptive Source-Channel Coding with Feedback for Progressive Transmission of Medical Images

Cited by 6 publications

References 23 publications

Enhanced image transmission with error control

Enhanced image transmission with error control

Image transmission quality analysis over adaptive Reed-Solomon coding

Joint Source/Channel Coding for Prioritized Wireless Transmission of Multiple 3-D Regions of Interest in 3-D Medical Imaging Data

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