This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched...This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched pixels and the relationship between matched pixels. The modified EMR introduces the new concept of generalized acreage to measure the overlaying parts between the target image and the model. It also defines similarity of local occlusion and of local dithering to measure interference degree. Not only edge points are considered but also non-edge points, occlusion, and dithering. Using the same preprocessing, the experiments match images based on tra-ditional EMR and the proposed EMR separately. Based on the proposed EMR the paper achieves more stable registration and higher precision.展开更多
A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generat...A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.展开更多
基金Supported by the National Natural Science Foundation of China(No.60802045)the Fundamental Research Funds for the Central Universities(No.2009JBM020)the Strategy Alliance of Chinese Academy of Sciences for Guangdong Province(No.2010B090301014)China
文摘This paper proposes an enhanced Edge Matching Rate (EMR) to gain good image regis-tration based on Generalized Acreage (GA). Traditional EMR considers only matched pixels sum without concerns of the cause of unmatched pixels and the relationship between matched pixels. The modified EMR introduces the new concept of generalized acreage to measure the overlaying parts between the target image and the model. It also defines similarity of local occlusion and of local dithering to measure interference degree. Not only edge points are considered but also non-edge points, occlusion, and dithering. Using the same preprocessing, the experiments match images based on tra-ditional EMR and the proposed EMR separately. Based on the proposed EMR the paper achieves more stable registration and higher precision.
基金Supported by the National Natural Science Foundation of China (Nos. 40771176, 40721001)
文摘A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.
