高存储需求下车载多媒体图像分形压缩仿真

Fractal Compression Simulation of Vehicle-Borne Multimedia Images with High Storage Requirements

为增强车载多媒体服务质量,需要对车载多媒体图像进行压缩处理。针对传统压缩方法存在图像峰值信噪比和压缩比较低等问题,提出一种高存储需求下基于模糊聚类的车载多媒体图像分形压缩方法。解析图像分形压缩原理,并对车载多媒体图像进行图像灰度化和去噪等预处理,利用四叉树对处理后的图像进行值域块划分,基于模糊聚类算法遍历所有值域块,完成图像定义域块搜索,进而实现车载多媒体图像分形压缩。实验结果表明,与传统图像压缩方法相比,所提方法压缩后的车载多媒体图像图像压缩码率较高,分形压缩效果较好,且峰值信噪比分别提高7.08dB、8.62 dB、5.26 dB,压缩比提高8.9%、15.5%、91.55%,可见所提车载多媒体图像分形压缩方法具有一定的可靠性。

In order to improve the service quality of vehicular multimedia,it is necessary to compress the multimedia image.Due to low peak signal-to-noise ratio(PSNR)and low compression in traditional compression methods,this article presented a fractal compression method for vehicular multimedia images with high storage requirements based on fuzzy clustering.After the principle of image fractal compression was analyzed,the vehicular multimedia images were grayed and denoised,and then the range blocks of images were divided by quad tree.Moreover,all range blocks were traversed by fuzzy clustering algorithm,so that the domain block search was completed.Finally,the vehicular multimedia image fractal compression was achieved.Simulation results show that,compared with the traditional image compression method,the proposed method has higher compression code rate and better fractal compression effect for vehicular multimedia image.Respectively,the peak signal-to-noise ratio(PSNR)is increased by 7.08 dB,8.62 dB and 5.26 dB,and the compression ratio is increased by 8.9%,15.5%and 91.55%.It can be seen that the proposed method has certain reliability.