quantization is a core operation in lossy image compression. In the end-to-end learning-based image compression framework, quantization is conducted by a rounding operation during test, while it is replaced by additiv...
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ISBN:
(纸本)9781728198354
quantization is a core operation in lossy image compression. In the end-to-end learning-based image compression framework, quantization is conducted by a rounding operation during test, while it is replaced by additive uniform noise during training, leading to a mismatched problem between train and test. To address this problem, we propose a quantization error compensation method for the end-to-end learning-based image compression framework. The method uses Fourier series to approximate the periodic changes of the quantizationerror, and adds Laplacian noise to the quantized latent during test. The proposed method can be flexibly combined with different end-to-end learning-based image compression methods. Experimental results show that higher coding efficiency can be achieved by adding the proposed method with the state-of-the-art methods.
This paper proposes a novel data hiding method for JPEG 2000 coded images that embed multi-level information into quantized discrete wavelet transformed coefficients. Since the proposed method hides information repres...
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This paper proposes a novel data hiding method for JPEG 2000 coded images that embed multi-level information into quantized discrete wavelet transformed coefficients. Since the proposed method hides information represented as an integer to a transformed coefficient rounded to an integer, a JPEG 2000 code-stream conveying data keeps its standard JPEG 2000 code-stream structure. The proposed method is able to extract hidden data Without memorizing embedding positions;it thus Chooses transformed coefficients to which data is hidden freely. This characteristic makes the proposed method suitable for hiding data to a JPEG 2000 coded image with consideration of Region of Interest (ROI) coding that is a major feature. Simulation results show the effectiveness of the proposed method. (c) 2007 Wiley Periodicals, Inc.
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