一种PCA-FVQ和3D-SPECK结合的光谱图像分层编码方法

Yunfeng Yue, L. Zhuo, Suyu Wang, Yingdi Zhao, C. Shi
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引用次数: 1

摘要

本文提出了一种分层光谱图像编码方法。将光谱图像编码为两层,即基础层和增强层。首先,提出了一种PCA-FVQ(基于主成分分析的快速矢量量化)编码方法来生成基层比特流,并可以独立解码以提供基本的图像质量。然后利用3D-SPECK算法对基层比特流解码后的原始图像与重构图像之间的差值数据进行编码,生成增强层比特流,增强层比特流可以提供增强的图像质量。实验结果表明,在相同的编码条件下,与3D-SPECK算法相比,该方法在信噪比(Signal to Noise)方面的图像质量提高了1-15dB,同时压缩比可以得到精确控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A PCA-FVQ and 3D-SPECK combined hierarchical coding method for spectral imagery
In this paper, a hierarchical spectral imagery coding method has been proposed. The spectral imagery is encoded into two layers, i.e. base layer and enhancement layer. Firstly, an PCA-FVQ (Principal Component Analysis based Fast Vector Quantization) coding method has been proposed to generate the base layer bitstream, which can be decoded independently to provide a basic image quality. Then the differential data between the original image and the reconstructed image decoded from the base layer bitstream is encoded by 3D-SPECK algorithm to generate the enhancement layer bitstream which can provide an enhanced image quality. The experimental results show that, under the same coding conditions, compared with 3D-SPECK algorithm, the proposed method has achieved 1-15dB higher image quality improvement in terms of SNR (Signal to Noise) while the compression ratio can be controlled precisely.
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