A single CMOS image sensor based on a 0.35μm process along with its design and implementation is introduced. The architecture of an active pixel sensor is used in the chip. The fill factor of a pixel cell can reach 4...A single CMOS image sensor based on a 0.35μm process along with its design and implementation is introduced. The architecture of an active pixel sensor is used in the chip. The fill factor of a pixel cell can reach 43%,higher than the traditional factor of 30%. Moreover, compared with the conventional method whose fixed pattern noise （FPN） is around 0.5%, a dynamic digital double sampling technique is developed, which possesses simpler circuit architecture and a better FPN suppression outcome. The CMOS image sensor chip is implemented in the 0.35μm mixed signal process of a Chartered by MPW. The experimental results show that the chip operates welt,with an FPN of about 0.17%.展开更多
This paper introduces a car_borne road information collecting and updating system (LD2000) developed by Wuhan Technical University of Surveying and Mapping.This system is capable of collecting road network information...This paper introduces a car_borne road information collecting and updating system (LD2000) developed by Wuhan Technical University of Surveying and Mapping.This system is capable of collecting road network information and creating digital road network effectively by means of GPS,GIS and multi_sensor integration.The design and development of LD2000 system are also presented in this paper.展开更多
Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich textur...Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm(AGA) and Alternative Fuzzy C-Means(AFCM) . Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased,and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means(FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.展开更多
文摘A single CMOS image sensor based on a 0.35μm process along with its design and implementation is introduced. The architecture of an active pixel sensor is used in the chip. The fill factor of a pixel cell can reach 43%,higher than the traditional factor of 30%. Moreover, compared with the conventional method whose fixed pattern noise （FPN） is around 0.5%, a dynamic digital double sampling technique is developed, which possesses simpler circuit architecture and a better FPN suppression outcome. The CMOS image sensor chip is implemented in the 0.35μm mixed signal process of a Chartered by MPW. The experimental results show that the chip operates welt,with an FPN of about 0.17%.
文摘This paper introduces a car_borne road information collecting and updating system (LD2000) developed by Wuhan Technical University of Surveying and Mapping.This system is capable of collecting road network information and creating digital road network effectively by means of GPS,GIS and multi_sensor integration.The design and development of LD2000 system are also presented in this paper.
基金Under the auspices of National Natural Science Foundation of China (No. 30370267)Key Project of Jilin Provincial Science & Technology Department (No. 20075014)
文摘Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm(AGA) and Alternative Fuzzy C-Means(AFCM) . Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased,and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means(FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.
