在卫星上提取图像目标区域是降低传输数据量、提高空间传输链路利用率的重要一环。本文从小波系数相关性的角度, 提出一种针对空间图像压缩算法 (CCSDS-IDC)的目标区域提取方法, 是以图像小波系数 LL3子带为起点, 以四叉树分解为基础的自适应非均匀矩形分割与合并 (ANURSM), 将对应背景区域的小波系数与对应目标区域分离。经试验表明, 算法能够准确、有效地提取出图像目标区域对应的小波系数, 与改进的 CCSDS-IDC相结合能够有效降低传输数据量并提高图像目标区域质量。

High-resolution remote sensors and equipments collected far more images than transmitted through limited-band downlink channels. There is a critical need for special target detection algorithm to select subset of the image collection effectively. An adaptive non-uniform rectangular segmentation and merging algorithm (ANURSM) is proposed to meet the requirement. The algorithm extracts coefficients corresponding to target-area from background in LL3 subband of wavelet-transformed images, and can be integrated with CCSDS-IDC (The Consultative Committee for Space Data Systems-Image Data Compression Recommended Standard) easily and seamlessly. Experiments have demonstrated that the algorithm can effectively reduce data volume and improve the quality of target areas in images.