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Adaptive DCT coding of images using entropy-constrained trellis coded quantization

机译:使用熵约束网格编码量化的图像自适应DCT编码

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An adaptive DCT (discrete cosine transform)-based image coding scheme is developed in which a combination of a perceptually motivated image model, entropy-constrained trellis coded quantization (ECTCQ), and perceptual error weighting is used to obtain good subjective performance at low bit rates. The model is used to decompose the image into strong edge, slow-intensity variations and texture components. The perceptually important strong edges are encoded essentially losslessly. The remaining components are encoded using an adaptive DCT in which the transform coefficients are quantized by ECTCQ. The contrast sensitivity of the human visual system is used for perceptual weighting of the transform coefficients. Objective and subjective results suggest noticeable improvement over JPEG (Joint Photographic Experts Group).
机译:提出了一种基于自适应DCT(离散余弦变换)的图像编码方案,该方案将感知动机图像模型,熵约束网格编码量化(ECTCQ)和感知错误权重相结合,以在低位获得良好的主观表现。费率。该模型用于将图像分解为强边缘,慢强度变化和纹理分量。感知上重要的强边缘基本上无损编码。其余分量使用自适应DCT进行编码,其中,变换系数通过ECTCQ进行量化。人类视觉系统的对比度灵敏度用于变换系数的感知加权。客观和主观结果表明,与JPEG(联合图像专家组)相比,有了明显的改进。

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