篇名 |
Compressive Perception Image Reconstruction Technology for Basic Mixed Sparse Basis in Metal Surface Detection
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並列篇名 | Compressive Perception Image Reconstruction Technology for Basic Mixed Sparse Basis in Metal Surface Detection |
作者 | Xiang-Yun Yi、Xiao-Bo Dong、Liang-Gui Zhang、Yan-Chao Sun、Wen-Tao Li、Tao Zhang |
英文摘要 | Applying Compressed Sensing (CS) technology to robot vision image transmission, an effective method for image reconstruction in robot imaging is proposed to improve the accuracy of reconstruction. Reconstructing images using a mixed sparse representation of DCT and circularly symmetric contour wave transform, the basic algorithm used is the Smoothed Projection Landweber (SPL) algorithm, which optimizes the coefficients under different sparse transformations by incorporating hard thresholding and binary thresholding methods for different sparse bases during iterations. The experiment shows that compared with single sparse base image reconstruction, the proposed reconstruction method has improved reconstruction accuracy.
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起訖頁 | 159-165 |
關鍵詞 | obot vision、mixed sparse basis、reconstruction accuracy、SPL |
刊名 | 電腦學刊 |
期數 | 202402 (35:1期) |
DOI |
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| Small Object Detection in Remote Sensing Based on Contextual Information and Attention |
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| A Method for Industrial Robots to Grasp and Detect Parts of Instrument under 3D Visual Guidance |