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There are many non-uniformity factors for the original array time delay integral CCD sweep image. Firstly, the non-uniformity characteristics such as parallel detector direction, vertical detector direction and multi-detector are counted. According to the difference of the regular response caused by the inconsistent response of the detector and the dimming of the optical system, the multiplicative original image obtained under similar conditions is used to statistically calculate the multiplicative component of the non-uniform correction coefficient of each pixel in the detection direction. The change of the attitude of the platform and the difference of the atmospheric reflection energy cause the difference of the radiation in the sweeping direction. For each original image, the additive component of the non-uniform correction coefficient of each line of the sweeping direction is calculated. Then, the multiplicative component and the additive component are used to the linear array. The original image of the camera is quickly corrected pixel by pixel. For the multi-line array detector splicing camera, the multi-detector image is automatically seamlessly spliced by the uniform processing of overlapping pixels.

Traffic plays a vital role in people's life and social economy.Vehicle speed detection is an important part of intelligent transportation system.This paper focus on the vehicle speed detection based on multi-source data from autonomous unmanned aerial vehicle (UAV).Firstly,we build a multi-source data acquisition system on UAV for visible image and thermal infrared image.Secondly,we utilize "You only look once" (YOLO),which is a deep learning framework for vehicle detection.Finally,we track the vehicle based on Kalman filter and calculated the vehicle speed according to the result of vehicle tracking.This paper adopts the UAV platform to increase the flexibility.While the use of multi-source data improves the accuracy of the vehicle detection and tracks the vehicle in different illumination.The result of experiments shows that the strategy is effective and robust,which provides an efficient and flexible monitoring mode for traffic management department.

Back projection is the key technology for rectification of linear array CCD imageries. On the basis of analyzing the imaging mode and characteristics of linear whiskbroom image, a back projection algorithm based on the constraints of object-space relation was proposed, aiming at the inefficiency of conventional image-based sequential or iterative search methods. The best scan-line of the adjacent point was used as a priori value, to estimate the number of the scan-lines between the adjacent point and the current point, thus locating the initial best scan-line. Then, a search window was constructed by the center of the initial best scan-line, and an accurate searching was implemented. At last, according to the orientation elements of the best scan-line, the coordinates back projection was carried out. The feasibility, accuracy and efficiency of the proposed method were verified by the experimental results of the airborne linear array whiskbroom simulated image data and the pushbroom real image data.

The management and application of remotely sensed data has become much more difficult due to the dramatically growing volume of remotely sensed imagery. To address this issue, content-based image retrieval (CBIR) has been applied to remote sensing image retrieval for information mining. As a consequence of the growing volume of remotely sensed imagery, the number of different types of image-derived products (such as land use/land cover (LULC) databases) is also increasing rapidly. Nevertheless, only a few studies have addressed the exploration and information mining of these products. In this letter, for the sake of making the most use of the LULC map, we propose an approach for the retrieval of alike scenes from it. Based on the proposed approach, we design a content-based map retrieval (CBMR) system for LULC. The main contributions of our work are listed below. Firstly, the proposed system can allow the user to select a region of interest as the reference scene with variable shape and size. In contrast, in the traditional CBIR/CBMR systems, the region of interest is usually of a fixed size, which is equal to the size of the analysis window for extracting features. In addition, the user can acquire various retrieval results by specifying the corresponding parameters. Finally, by combining the signatures in the base signature library, the user can acquire the retrieval result faster.