Block truncation coding (BTC) is an efficient and fast lossy image coding technique.
块截短编码(BTC)是一种快速有效的有损图像编码技术。
This paper proposes a new block matching criterion called the bit-correlation matching function for sequence image coding.
本文提出了一种新的序列图象编码块匹配准则——比特位相关匹配函数。
Taking the Brownian dimension as their texture feature, image blocks were clustered and sorted, to control the number of domain blocks to be compared with each range block in coding.
以图像的布朗维数为纹理特征对编码中的图像块进行聚类和排序，实现了对每个值域块所需比较定义域块数目的精确控制。
Quantized affine transformation t constitutes the fractal block coding of the image block.
量化后的仿射变换t构成了图像块的分形块编码。
Disparity estimation and compensation are vital tasks in stereo image coding. An algorithm for disparity estimation and compensation based on overlapped block matching is proposed in this paper.
视差估计与补偿是立体图像编码的关键问题，本文提出了一种基于交叠块匹配的视差估计与补偿算法。
The dissertation proposes a novel adaptive block-size stereo image coding algorithm based on traditional block-based coding algorithm, which fully utilizes the information of intensity variety.
论文研究了传统的基于块匹配的立体图像编码方法，在此基础上，提出了一种新的利用亮度变化信息的自适应块匹配立体图像编码算法。
Reducing fractal block coding time is one of the main problems of fractal image compression.
缩短分形块编码时间是进行分形图象压缩的关键问题之一。
It consists of error-resilient image coding and post-processing error concealment. The former prevents errors from propagating across image block boundaries with little overhead.
该方法由错误弹性图像编码和后处理错误隐匿两部分组成，错误弹性图像编码利用图像块头有效地避免了错误在图像块之间的蔓延。
Block truncation coding (BTC) is a fast lossy image compression technique.
块截短编码(BTC)是一种基块的快速有损图象压缩技术。
A method is presented here for color image compression which is based on efficient combination of Block Truncation coding (BTC) and Principal Component Analysis (PCA).
本文提出的彩色图象压缩方法基于BTC(块截断编码)和PCA(主成分分析)的有效结合。
Image and template are matched by comparing their R-block coding.
然后通过各个R -块编码值的比较，实现图像与模板的匹配。
Image and template are matched by comparing their R-block coding.
然后通过各个R -块编码值的比较，实现图像与模板的匹配。
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