30 results about "Fast ica" patented technology

The invention discloses a method for objectively evaluating the quality of a three-dimensional image without a reference. According to the method for objectively evaluating the quality of the three-dimensional image without the reference, in the training stage, multiple original undistorted three-dimensional images and corresponding distorted three-dimensional images are selected to form a training image set, then dictionary training is conducted according to the Fast-ICA method, so that the visual dictionary table of each image in the training image set is constructed, and visual quality tables corresponding to the visual dictionary tables are constructed by calculating the frequency responses of each pixel point in each original undistorted three-dimensional image and each pixel point in the corresponding distorted three-dimensional image in the training image set under the conditions of different center frequencies and different directional factors; in the testing stage, for the tested three-dimensional image, a predicted objective evaluation value of the quality of the tested three-dimensional image is obtained by calculating the frequency responses of each pixel point in the tested three-dimensional image under the conditions of different center frequencies and different directional factors according to the constructed visual dictionary tables and the constructed visual quality tables. The method for objectively evaluating the quality of the three-dimensional image without the reference has the advantages that calculation complexity is low, and the relevancy between objective evaluation results and subjective sensing is high.

The invention relates to a J-wave detection and classification method, in particular to a J-wave detection and classification method based on Q-switched wavelet transform and high-order cumulants. The present invention first collects ECG data through an electrocardiograph, obtains two types of normal signal and J wave signal, uses stationary wavelet transform to detect R peak point, and intercepts 128 points after R point as initial data samples. Apply stationary wavelet transform and Q-switched wavelet transform to decompose initial samples and extract feature vectors. Input feature vectors to ensemble C4.5 decision trees. Then extract the feature vector of the test sample according to the above process, input it to the trained integrated C4.5 decision tree, and obtain the category attribute of the test sample. The present invention can more simply and conveniently obtain a feature vector with a lower dimension that is highly representative of the original signal through serial fusion and rapid ICA dimension reduction, and input it to the integrated decision tree classifier, which can be fast and efficient To realize the accurate classification of J wave signal.

The invention discloses a no-reference fuzzy distorted stereo image quality evaluation method, which comprises the following steps: in a training stage, selecting a plurality of undistorted stereo images and corresponding fuzzy distorted stereo images to form a training image set; then, carrying out a dictionary training operation by a Fast-ICA (independent component analysis) method, and constructing a visual dictionary table of each image in the training image set; constructing the visual quality table of the visual dictionary table of each distorted stereo image by calculating a distance between the visual dictionary table of each undistorted stereo image and the visual dictionary table of each corresponding fuzzy distorted stereo image; in a testing stage, for any one tested stereo image, carrying out non-overlapping partitioning processing to a left sight point image and a right sight point image of the tested stereo image; and according to the constructed visual dictionary table and the constructed visual quality table, obtaining an objective evaluation prediction value of the image quality of the tested stereo image. The no-reference fuzzy distorted stereo image quality evaluation method has the advantages of low computation complexity and good relevance between an objective evaluation result and subjective perception.