基于心理视觉冗余和PCA的图像压缩算法

为了进一步提高图像的压缩率,提出了基于心理视觉冗余和主成分分析(PCA)的图像压缩算法。根据人类视觉处理过程中各种信息的重要程度不同的原理,在不影响图像的感知质量的前提下,通过消除不重要的心理视觉冗余信息;再用PCA对消除心理视觉冗余的图像做进一步降维,使得图像数据进一步压缩。通过实验结果可知,提出的新的压缩算法在不影响图像感知质量的前提下,使得图像压缩比提高了1倍,大大缩小了存储空间。

Image Compression Algorithm Based on Psychological Visual Redundancy and PCA

In order to improve the compression rate of high-quality image, the Image Compression Algorithm based on psychological visual redundancy and Principal Component Analysis was proposed. According to the principle of various types information with different significance degrees in the human visual process, the unimportant psychological visual redundant information was eliminated under it did not affect the perceived quality of the image, reducing the dimension of image that eliminated mental visual redundancy with PCA which made a progress in image compression. The experimental results show that the proposed new compression algorithm makes the image compression ratio increased by 1 times under it does not affect the perceived quality of the image and greatly reduces the storage space.