【摘要】 从灰度图像的局部统计特性出发 ,提出了基于四叉树的灰度图像压缩方法。该方法的基本思想是 ,如果当前原始子块的最大灰度差小于一给定阈值 ,则把当前原始子块视为一个整体子块 ;否则把当前原始子块一分为 4 ,得到 4个大小相等的更小的原始子块。该方法把原始图像分解为若干个整体子块 ,并采用有效的方式存储每个整体子块的位置、大小和灰度 ,从而达到压缩的目的。采用合理的平滑算法 ,有效地消除了解码图像中的方块效应。计算机仿真实验表明 ,该方法可以获得较高的压缩比和峰值信噪比 ,可以很好地保持原始图像中灰度变化较大的细节 ,可以方便地去除方块效应 ,具有较高的实用价值。更多还原

【Abstract】 Based on the local statistical property of gray image, the compression method for gray image is investigated. The basic point is that, if the maxim difference of gray value of the current original sub-block is lower than a given threshold, the current original sub-block can be considered as an integral sub-block, otherwise the original sub-block is decomposed into four smaller original sub-block with the same size. In so doing the original image is decomposed into lots of integral sub-blocks, and the position, size and gray value of each integral sub-block can be stored with an efficient way, so as to achieve the aim of compression. The method of this paper uses reasonable smoothing algorithm, and removes block-effect satisfactorily. Computer simulation experiments show that the method can gain higher CR (compression-rate) and PSNR (peak-signal-noise-rate), keep details where pixel gray value varies hugely, remove block-effect conveniently, and have higher practical value.更多还原