改进的矩形NAM图像表示算法

为了提高图像的表示效率，提出了一种改进的矩形非对称逆布局模式表示模型(NAM)图像编码算法IRNAM。该算法采用双矩形子模式对灰度图像进行表示，结合位平面优化策略，并顺序存储各子模式的数据，使得子模式数目大幅减少。实验结果表明：与矩形NAM算法和其他改进的NAM算法相比, IRNAM算法使表示图像的子模式数明显减少了，从而有效地节省了数据存储空间,是一种高效的图像表示方法。

Improved rectangle NAM algorithm for image representation

In order to improve image representation efficiency, an improved rectangle Non-symmetry Anti-packing representation Model (NAM) named IRNAM was proposed for image coding. This scheme adopted double-rectangle sub-patterns to represent gray image, integrated bit plane optimization strategy and stored the sub-patterns continuously, thus the number of sub-patterns had decreased sharply. The experimental results show that compared with rectangle NAM algorithm and other improved NAM algorithms, the number of sub-patterns can be reduced apparently after employing IRNAM algorithm, which can save data storage space effectively and prove to be a high performance image representation method.