由于图像经低通滤波削弱高频分量之后，其小波变换系数将具有更好的能量聚集性，为此对基于这一原理的结合平滑预处理的近无损压缩方案进行深入研究。为了获得更好的平滑性能，以提高此近无损压缩方案的压缩比，提出了一种新的图像平滑算法。该算法在遍历过程中，根据各像素水平方向和垂直方向的梯度强度，通过自适应地选择合适的滤波方向来对图像进行平滑，取得了很好的平滑性能。该算法的另一个显著优势就是能够根据指定的最大幅度误差参数进行相应的平滑处理，从而实现了精确度可选的近无损压缩。另外，该算法不仅计算复杂度低，且易于实现。多幅标准测试图像的实验结果表明，该算法是有效的，且具有良好的适应性。

The wavelet coefficients of an image will obtain higher performance of energy concentration after its high frequency components are decreased by low pass filters. This paper makes a study of the near lossless compression scheme based on this principle. In order to make smoothing process more effective to improve compression rate of the above near lossless compression scheme, this paper presents a novel smoothing algorithm, which can achieve better smoothing performance by adaptively select appropriate filter direction for every pixel according to its horizontal and vertical gradient intensity in the process of scan. Another remarkable advantage of this algorithm is that it can smooth the image according to given maximum amplitude error, then makes the accuracy of near lossless compression adjustable. In addition, this algorithm is easy to implement for its low computation complexity. The experimental results with several standard test images demonstrate the effectiveness and adaptability of the presented algorithm in this paper.