摘要
提出了一个基于ＤＣＴ和二维多项式近似的块分类编码算法。在该算法中，原始图象被分割成互不覆盖的８×８子块。通过依次地利用灰度局部方差、二维多项式近似误差和图象信号的空间频率分布，把图象块分为均匀、平滑、粗糙和细节４类。均匀块和平滑块分别采用零阶和一阶多项式近似。粗糙和细节块先进行ＤＣＴ变换，然后对其ＤＣＴ系数量化后采用改进的游程编码表示。实验结果表明该算法具有良好的性能。在未采用熵编码为编码码流作后处理的情况下，性能仍优于ＪＰＥＧ标准。
Classified Block Coding has received more attention recently for the advantage of easy implementation. The classification and coding of blocks are the two important problems in classified block coding.In this paper, we propose a classified block coding algorithm based on DCT coding and polynomial approximation. In the algorithm, the original image is splitted into nonoverlapped 8×8 blocks. The blocks are classified into four classes: constant blocks, smooth blocks, coarse blocks and detail blocks, by using the intensity local variance, the polynomial approximation error and spatialfrequency distribution. The constant blocks and smooth blocks are approximated by 0order and 1order polynomial respectively. For the coarse and detail blocks, we compute and quantize their DCT coefficients. Then encode them by means of an improved runlength coding. The experiment results show that the proposed algorithm, without using entropy coder as postprocessor of the codes, has better performance than JPEG.
出处
《中国图象图形学报（A辑）》
CSCD
1997年第12期890-894,共5页
Journal of Image and Graphics
基金
国家攀登计划"认知科学中若干重大前沿问题的研究"课题
关键词
块分类编码
DCT
多项式近似
图象块编码
Classified block coding, DCT, Polynomial approximation, Local variance
