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GaoFen1 is the first high-resolution earth observation satellite built in China, and carries four wide field-of-view (WFV) cameras to achieve large-scale monitoring and mapping. However, the unstable attitude measurement accuracy of the satellite generally imparts low geopositioning accuracy and inconsistent geometric error in overlapping areas of WFV images. A feasible and effective large-scale planar block adjustment (PBA) method is presented that corrects the geometric errors of the vast WFV images integrally, further improving the geometric accuracy of these images. In addition, whether ground control points (GCPs) are needed, and the effect of different numbers of GCPs on PBA accuracy is also investigated. Two key technologies are used in this paper. First, a universal PBA error equation based on the virtual control points is presented to allow PBA with or without GCPs. Second, an adjustment method aided by a digital elevation model is adopted to overcome the weak convergence geometry among WFV images, further ensuring stable estimation of PBA. The effectiveness of the proposed method was verified by 664 WFV images covering most of mainland China. The satisfactory experimental results indicate that the method presented herein is reasonable and effective, but that a certain number of GCPs is needed to ensure the accuracy of large-scale PBA results for WFV images. [ABSTRACT FROM AUTHOR]

The article focuses on the research about image recognition, considered an important branch of artificial intelligence (AI), conducted in China. It notes that the fundamental research and practical applications of image recognition started in China during the 1960s, reaching 50 years. The fundamental researches include the integration of statistical and syntactic pattern recognition, the introduction of artificial neural networks (ANNs), and the analysis of high-dimensional data. Meanwhile, it notes that the years intended by Chinese researchers on image recognition application helped them to achieve significant developments including the introduction of the optical character recognition, a reliable identity authentication technology, and the intelligent transportation systems (ITS).

The article discusses the biological application associated with molecular imaging, including pathology, clinical diagnostics, monitoring and efficacy evaluation in the treatment of cancers or other fatal diseases. The reported progress of the research in molecular imaging shows that there are critical challenges that need to be addressed and improving the image qualities is one of the urgent tasks, including the development of a high-quality contrast agent. Moreover, it states that it is difficult and time consuming to integrate molecular studies.