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The single-pass perceptual embedded zero-tree coding implementation on DSP

机译:DSP上的单遍感知嵌入式零树编码实现

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This paper proposes a block-edge-based Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC) method. SPPEZC combines two novel compression concepts, called Block-Edge Detection (BED) and the Low-Complexity and Low-Memory Entropy Coder (LLEC), for coding efficiency and quality. Because the edge information can provide beneficial cues for preserving the perceptual quality of compressed images, this paper presents an effective combinative coding scheme, called Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC), which integrates the improved LLEC and the block-edge information. This approach provides improved perceptual quality in compressed images. Based on the block-edge information, this paper proposes an adaptive architecture for adjusting the quantization table and subsequently coding the quantized coefficients with the LLEC. The proposed SPPEZC approach was implemented and evaluated on both PC-based and DSP-based embedded platforms. Experimental results and comparisons demonstrate that the proposed SPPEZC technique provides computational efficiency as well as satisfactory perceptual quality in compressed images.
机译:本文提出了一种基于块边缘的单遍感知嵌入零树编码(SPPEZC)方法。 SPPEZC结合了两种新颖的压缩概念,称为块边缘检测(BED)和低复杂度和低内存熵编码器(LLEC),以提高编码效率和质量。由于边缘信息可以为保留压缩图像的感知质量提供有益的线索,因此本文提出了一种有效的组合编码方案,称为单遍感知嵌入式零树编码(SPPEZC),该方案将改进的LLEC和块边缘集成在一起信息。这种方法可提高压缩图像的感知质量。基于块边缘信息,本文提出了一种自适应体系结构,用于调整量化表并随后使用LLEC对量化系数进行编码。 SPPEZC方法在基于PC和基于DSP的嵌入式平台上均已实现和评估。实验结果和比较结果表明,提出的SPPEZC技术在压缩图像中提供了计算效率以及令人满意的感知质量。

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