"基于特征的图像拼接技术研究及应用"
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Image mosaics involve aligning and merging a series of overlapping images to create a new image that contains a wide-angle, complete, and high-definition view of the scene. This technology is crucial in the field of digital image processing and finds extensive applications in photogrammetry, computer vision, remote sensing, medical image analysis, computer graphics, and more. Image mosaics face challenges such as differences in imaging system characteristics, shooting angles, and time, as well as noise interference and occlusion, making the process difficult. There are different approaches to image mosaics, including feature-based, grayscale-based, and transform-domain-based methods. Feature-based image mosaics are less affected by factors like lighting and rotation, and they involve a smaller number of features compared to pixels, thus enhancing speed and efficiency. This makes feature-based methods the most popular approach in image mosaics. This study focuses on feature-based image stitching using a point-to-line method. Experimental results demonstrate the effectiveness of this approach in achieving high-quality image stitching. Key words: image mosaics; image registration; image fusion; point-to-line method.
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