Remote-Sensing Image Compression Using Two-Dimensional Oriented Wavelet Transform

In this paper, a 2-D oriented wavelet transform (OWT) is introduced for efficient remote-sensing image compression. The proposed 2-D OWT can perform integrative oriented transform in arbitrary direction and achieve a significant transform coding gain. To maximize the transform coding gain, two separable 1-D transforms are implemented in the same direction for local areas with direction consistency. Subpixel interpolation rules are designed for rectangular subbands generation. In addition, semidirection displacement is adjusted to handle direction mismatch after the first 1-D transform. Experimental results demonstrate that the proposed 2-D OWT compression scheme outperforms JPEG2000 for remote-sensing images with high resolution, up to 0.43 dB in peak signal-to-noise ratio (PSNR), 0.0261 in the measure of structural similarity, 0.44% in Kappa coefficients, respectively, and significant subjective improvement. Meanwhile, it outperforms JPEG2000, previous adaptive directional lifting and weighted adaptive lifting methods, up to 1.98, 0.36, and 0.19 dB in PSNR for natural images. Furthermore, it is suitable for real-time remote-sensing processing for its low computational cost.