| Summary: | 碩士 === 國立臺灣大學 === 電信工程學研究所 === 105 === In recent years, image fusion has become an important issue in image processing community. The target of image fusion is to generate a composite image by integrating the complementary information from multiple source images of the same scene[1].
Image fusion play a role of enhancing the perception of a scene by combining detail information captured by different imaging sensors.For system, the input source images can be acquired from either different types of imaging sensors or a sensor whose optical parameters can be changed, e.g., at different exposure levels, at different focus levels, at different light source. And the output called fused image will be more suitable for human or machine perception than any individual source image. Image fusion has been used as an effective tool for many important applications, which include medical imaging, microscopic imaging, remote sensing, computer vision, and robotics.
Besides, I revised the disadvantage of traditional Saliency Detection algorithm and made a combination of Image Subtraction concept to solve the defect of redundant detection named “Boosting Saliency Detection with Image Subtraction (BSD)”.Furthermore, Boosting Saliency Detectionis applied to recognize the noticeable part in image. I attempted to make use of the system on video detection. Using BSD, we can extracteach of saliency part in each frame, which represent moving object in the video.
Last, I integrated both of Exposure Image Fusion and Boosting Saliency Detection algorithm to reach the final goal of moving object tracking with image quality enhancement. And present some applications in trajectory of ball in sport field and motion tracking under the monitor
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