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 non-overlapped 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 spatial-frequency distribution. The constant blocks and smooth blocks areapproximated by 0-order and 1-order polynomial respectively. For the coarse and detail blocks, we compute and quantize their DCT coefficients. Then encode them by means of an improved run-length coding. The experiment results show that the proposed algorithm, without using entropy coder as postprocessor of the codes, has better performance than JPEG.