摘要
利用视频图像信号在DCT(Discrete Cosine Transform,DCT)域的稀疏特性,引入了压缩感知(Compressed Sensing,CS)理论并应用于视频编解码与重构中,给出了基于DCT域的高质量编码与重构图像的新方法,设计完成CS重构的图像编、解码流程,并构建实际应用系统。实验表明:对于具备稀疏特性的图像,在图像编、解码系统中可以结合CS理论与方法,能得到较高质量的重构图像,比仅采用DCT和IDCT的方法其峰值信噪比PSNR也有较大提高。
Utilizing the sparsity of video images in the DCT domain, compressed sensing is applied to the coding and reconstruction of video images： A new method of coding and reconstructing high quality images in DCT domain is formulated. In this paper, image coding and decoding process to realize the CS reconstruction is given, and a practi- cal application system is designed. The experimental results show that the image with sparsity, the image coding and decoding system integrated with CS theory and its methods can be used to obtain reconstructed images with high quality, and compared with DCT and IDCT, the method has some improvement in the term of PSNR for general images.
出处
《湖南第一师范学院学报》
2013年第3期106-109,共4页
Journal of Hunan First Normal University
