2D video three-dimensional method based on sample learning and depth image transmission
A deep image and sample learning technology, applied in the field of video processing, can solve the problems of image boundary distortion, large computing time, and difficulty in ensuring the continuity of 3D images, etc., to achieve edge preservation, edge texture definition improvement, and internal smoothness Effect
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[0041] refer to figure 1 , the implementation steps of the present invention are as follows:
[0042] Step 1. Extract image features
[0043] 1a) Input two 2D video images I with a size of 320×240 1 and I 2 , and extract the video image I 1 Histogram eigenvectors of oriented gradients Specific steps are as follows:
[0044] (1a1) convert the video image I 1 It is divided into units with a size of 40×40, and the gradient histograms of 9 directions are counted in each unit, and four adjacent units form a block with a size of 80×80, and the gradient histograms of the four units in a block are connected to obtain The gradient histogram feature vector of the block;
[0045] (1a2) Concatenating the gradient histogram feature vectors of all blocks, the resulting video image I 1 Histogram eigenvectors of oriented gradients H I 1 → .
[0046] 1b) Extract all ...
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