一种改进的遥感图象准无损压缩JPEG-LS算法

An Improved Algorithm of JPEG-LS for Near-lossless Compression of Remote Sensing Images

为适应遥感图象较高倍率准无损压缩的需要 ,改进了 JPEG- L S算法 ,该算法首先通过放宽游程检测门限 ,并通过引入局部梯度控制下的预测来增加平均游程长度 ,以提高压缩比 ;然后通过在游程编码区域附加误差修正编码及通过重构图象平滑滤波来改善重构图象的目视效果和提高 PSN R值 ;最后 ,采用 Golomb- Rice Coding技术来对越界误差进行编码 ,以保持 JPEG- L S算法误差界可控的优点 .综合利用以上措施 ,在相同单像素误差界 (±7)下 ,不仅压缩比略有提高 ,而且重构图象的视觉效果得到明显改善 ,PSN R提高约 1～ 3d B.

In this paper, an improved JPEG-LS algorithm is proposed to meet the needs of higher near-lossless compression ratio for remote sensing images. First, the threshold magnitude for run-length coding is increased and a prediction based on the control of local gradient is employed to extend the average run-length value, and this results in higher compression ratio. Second, because the subjective quality of the reconstructed image compressed by JPEG-LS at higher ratio degrades quickly, an error-modifying approach is added to the run-length coding area and a smoothing filter is applied to the reconstructed image. Thus the rebuilt image when observed by human eyes is much better and the objective quality measured by PSNR is higher as well. Finally, Golomb-Rice Coding method, which is a part of the original JPEG-LS, is adopted to encode residual errors. This can control the maximum absolute error of every pixel value in the rebuilt image and therefore keeps the great advantage of the original JPEG-LS in the sense of error control style. Integrating the above measures into a software package, under the same limit of ±7 for maximum absolute error of every pixel value, not only the compression ratio is somewhat increased, but also the human visual perception is obviously improved in the comparison with JPEG-LS. In our experiments, PSNR is about 1～3dB higher.