基于DPCM与S+P变换的图像无损压缩

S+P变换是由AmirSaid犤7犦提出的一种多分辨表示方法,能够实现整数到整数的变换,从而成功地应用于图像的无损压缩,其性能优于基于线性预测的JPEG标准。为了进一步提高压缩性能,论文提出了一种基于DPCM与S+P变换的图像无损压缩算法。首先,对原始图像进行线性预测,得到差值图像;其次,对差值图像进行S+P变换;最后,对变换系数进行熵编码压缩。新算法利用像素间的相关性,给出了一种新的利用一维S+P变换实现图像变换的方法,减少了变换增加的数据量,有效地解决了边界处理问题。实验结果与性能比较表明:新算法有效的,优于其它著名的基于多分辨分解的无损图像压缩编码算法犤7,10,12犦。

Lossless Compression of Images Based on DPCM and S+P Transform

S+P transform proposed by Amir Said7is an efficient multiresolution representation method.It can map integers to integers,so it has been used in lossless compression of images with better performance than that of JPEG standard based on linear prediction.To further improve compression performance,this paper presents an efficient lossless compression algorithm of images based on DPCM and S+P transform.Firstly,an error image is obtained from an original image with linear prediction;Secondly,the error image is transformed with S+P transform;Finally,the transformed coefficients will be compressed effectively with entropy coding.In addition,our algorithm proposes a new method to transform images with one-dimensional S+P transform,which can reduce the number of the added data produced from transform,and solve boundary problems efficiently.We list our software simulation results,which are compared with those of other known algorithms7,10,12 for multiresolution-based lossless compression.The comparison shows that the new method is effective and efficient,and produces the best results.