其他摘要 | With the development of space remote sensing technology, the resolution of optical remote sensing image is more and more high, and the data obtained in a short period is increasing. However, the backward technology of transmission and storage for remote sensing can’t meet the increasing image data. So, the images should be compressed before being transmitted. Usually, people only focus on a small part of an image, which is called region of interest, while the other parts known as background region. When compressing an image, lossless compression or loss compression with a low ratio for the region of interest can be adopted, and the background region can be compressed using loss compression with a high ratio. As a result, it not only reduces the requirements of the image transmission bandwidth, and also reduces the loss of detail information of region of interest. The paper mainly studies on ROI compression algorithm based on CCSDS, and tries to detect the regions of interest of remote sensing images with itti’s model, which is one of the models based on visual attention mechanism.Itti′s model is applied to detect the ship targets, which is considered as the region of interest of ocean surveillance satellite images. It illustrates the algorithm process of Itti′s model: firstly, the saliency map is obtained with the fusion of remote sensing image features, such as colors, intensity , orientations and so on; Secondly, the focus of attention is extracted using the mechanism of winner-take-all and inhibition of return; finally, setting the focus of attention as the center, a circular salient region with a fixed radius is obtained. The paper introduces a capacitor array charging model to describe the extracting and transferring process of the focus of attention, and also introduces the discrete moment transform to enhance the response of image texture features. Then, the threshold segmentation method is chosen to extract the salient region with the focus of attention. it is verified that both the shape and size of the salient region are consistent well with the ship targets; the background contained in the salient region is also reduced significantly. Moreover, the improved algorithm has a good real-time performance. It comes to the conclusion that compared with Itti′s model, the improved algorithm is more effective and suitable for the extraction of ship targets detection of ocean satellite images.This paper introduces SPIHT, JPEG2000, CCSDS and so on. CCSDS divides the image into several segments, and each segment is coded independently. Different segments contain different information, equaling to the image texture complexity, which is measured by gradient in the paper. According to the value of the gradient, the paper allocates the rate in the way that the bigger the value of a segment gradient is, the more rate of the segment. The experiment shows that, the rate-allocating algorithm is beneficial to optimize the rate distortion performance of CCSDS.According to the characteristics of CCSDS, this paper presents a new ROI compression algorithm. After segmented, the region of interest and background of the image are compressed independently in the algorithm, which is implemented following the steps: firstly, the ROI mask is coded; secondly, the rate is allocated into the regions of interest and background based on the value of each region; thirdly, the regions of interest and background are coded. The experiment shows that, the algorithm can improve the recovery effect of the regions of interest. |
修改评论