JOURNAL ARTICLE

Selective Error Detection for Error-Resilient Wavelet-Based Image Coding

Lina J. KaramTuyet-Trang Lam

Year: 2007 Journal:   IEEE Transactions on Image Processing Vol: 16 (12)Pages: 2936-2942   Publisher: Institute of Electrical and Electronics Engineers

Abstract

This paper introduces the concept of a similarity check function for error-resilient multimedia data transmission. The proposed similarity check function provides information about the effects of corrupted data on the quality of the reconstructed image. The degree of data corruption is measured by the similarity check function at the receiver, without explicit knowledge of the original source data. The design of a perceptual similarity check function is presented for wavelet-based coders such as the JPEG2000 standard, and used with a proposed "progressive similarity-based ARQ" (ProS-ARQ) scheme to significantly decrease the retransmission rate of corrupted data while maintaining very good visual quality of images transmitted over noisy channels. Simulation results with JPEG2000-coded images transmitted over the Binary Symmetric Channel, show that the proposed ProS-ARQ scheme significantly reduces the number of retransmissions as compared to conventional ARQ-based schemes. The presented results also show that, for the same number of retransmitted data packets, the proposed ProS-ARQ scheme can achieve significantly higher PSNR and better visual quality as compared to the selective-repeat ARQ scheme.

Keywords:
Computer science Retransmission Error detection and correction Wavelet Image quality Automatic repeat request Artificial intelligence Pattern recognition (psychology) Algorithm Hybrid automatic repeat request Transmission (telecommunications) Image (mathematics)

Metrics

4
Cited By
0.30
FWCI (Field Weighted Citation Impact)
17
Refs
0.62
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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