Meeting Arbitrary QoS Constraints Using Dynamic Rate Shaping of Coded Digital Video
NOSSDAV '95 Proceedings of the 5th International Workshop on Network and Operating System Support for Digital Audio and Video
Architectures for MPEG compressed bitstream scaling
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Perfect requantization for video transcoding
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Digital Video Transcoding for Transmission and Storage
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Toward optimal real-time transcoding using requantization in the DCT domain
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Dynamic rate shaping of compressed digital video
IEEE Transactions on Multimedia
Efficient scalar quantization of exponential and Laplacian random variables
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Processing JPEG-compressed images and documents
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Requantization for transcoding of MPEG-2 intraframes
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A mathematical analysis of the DCT coefficient distributions for images
IEEE Transactions on Image Processing
Recompression of JPEG images by requantization
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On optimal entropy-constrained deadzone quantization
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Low-complexity transform and quantization in H.264/AVC
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Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard
IEEE Transactions on Circuits and Systems for Video Technology
Rate-constrained coder control and comparison of video coding standards
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we provide an analysis of the requantization problem in order to improve the requantization process. This analysis is based on theoretical R-D results of requantized Laplacian sources instead of minimizing requantization errors as commonly found in the literature. We derive the effective quantizer characteristic by applying superposition to the quantizer characteristics of encoder and transcoder. Further investigation shows that the effective quantizer has a periodic property. Using the memoryless property of the probability distribution function and the periodic property of the effective quantizer characteristic, we derive expressions for entropy and distortion. Based on the theoretical R-D model, requantization for fine and coarse quantized signals is investigated. The analysis of the R-D behavior shows that a heuristic can be derived which improves the requantization process. Finally, the results from the R-D analysis are verified for requantization transcoding of H.264/AVC video streams. We show that the transcoding process for H.264/AVC video streams, which corresponds to coarse quantization, is improved with gains up to 1dB.