Face image super-resolution reconstruction recognition method based on multi-set canonical correlation analysis
A technique of super-resolution reconstruction and canonical correlation analysis, applied in image data processing, graphic-image conversion, character and pattern recognition, etc. View simultaneous mapping and other issues
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[0036] Such as figure 1The shown face image super-resolution reconstruction and recognition method based on multi-set canonical correlation analysis includes the following steps:
[0037] Step 1 In the training phase, use the training set to learn the correlation between views of different resolutions, divide each image in the training set corresponding to different resolutions into overlapping image blocks, use PCA to extract the principal component features of each image, and use MCCA Perform feature extraction, calculate the MCCA projection matrix, and project the principal component features of each image block to the consistent coherent subspace of MCCA;
[0038] The training phase in step 1 consists of the following steps:
[0039] (1) The training set of face images with multiple resolution views is given as where m is the number of resolution views, each image Divided into n overlapping o-pixel image blocks of size s×s, where N is the number of samples, is the s...
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