基于KL与小波联合变换的多光谱图像压缩

鉴于卫星拍摄的遥感图像的空间分辨率和光谱分辨率越来越高,在一些应用中,常会对多光谱图像进行压缩。为了提高多光谱图像的压缩质量,提出了联合相位相关和仿射变换的图像配准方法,有效提高了图像谱段之间的相关性。针对多光谱图像压缩,提出了结合Karhunen-Love,KL变换去除谱间相关和嵌入式二维小波编码方法。相比JPEG2000谱段图像独立压缩方法,提出方法解压图像的Peak Signal to Noise Ratio,PSNR值平均提高2.1 dB。实验结果表明:所提出的方法能在相同的压缩率下获得比JPEG2000谱段图像独立压缩方法更好的图像质量。

Multispectral image compression based on uniting KL transform and wavelet transform

In view of the fact that spatial resolution and spectral resolution of remote sensing images taken by satellite becomes more and more greater, in some applications, it is needed to compress the multispectral images. An image registration method by phase correlation and affine transformation was proposed in order to improve the multispectral image compression quality. The proposed method effectively improved the correlation between the image spectrums. Aiming at the multispectral image compression problem, the Karhunen-Love, KL transform method, which was used for eliminating correlation between spectrums in the image, and the low complexity two-dimensional wavelet encoding method were put forward. Compared with JPEG2000 independent compression method for each spectrum in an image, the Peak Signal to Noise Ratio, PSNR of decompression image by the proposed method improved 2.1 dB in average. Experimental results show that, under the same compression ratio, in this paper the proposed method can obtain better image quality than the JPEG2000 spectral image independent compression method.