2results about How to "Increase information entropy" patented technology

The invention discloses an infrared polarization multi-dimensional fusion imaging method based on nonlinear mapping, and belongs to the technical field of photoelectric detection and computational imaging. Performing Stokes vector solution on the input detection data to obtain a total intensity component, a polarization degree component and a polarization angle component; performing logarithmic domain mapping and gradient calculation on the total intensity component, and performing nonlinear enhancement based on local statistical characteristics on the polarization degree component to obtain an enhanced polarization degree; in an HSV color space, constructing a brightness component according to a logarithm domain mapping result, constructing a saturation component by combining the enhanced polarization degree and gradient information, constructing a hue component according to polarization angle information, and performing threshold constraint on the hue component based on the enhanced polarization degree; and a multi-dimensional fusion image is generated through color space inverse transformation from HSV to RGB. According to the method, background clutters are effectively suppressed, the image information entropy and the average gradient are remarkably improved, and high-contrast clear imaging of a weak and small target in a complex scene is realized.

This invention discloses a two-dimensional heterojunction array sensing method and device for high-precision monitoring of carbon pollution. The two-dimensional heterojunction array sensing method includes: emitting light signals with dynamically changing wavelength, power, and modulation frequency to a two-dimensional heterojunction array using a tunable light source according to a preset switching sequence; acquiring the electrical signals generated by the two-dimensional heterojunction array under the combined action of the target gas and the light signals, and converting the electrical signals into digital signals in multi-dimensional matrix form; and using a hybrid model integrating convolutional neural network branches and recurrent neural network branches to extract spatial pattern features and dynamic temporal features, ultimately outputting the type and concentration of the gas. This invention effectively solves the cross-sensitivity problem in gas identification by exciting the two-dimensional heterojunction array with optical sequence modulation and combining it with a lightweight neural network model, thus improving the identification accuracy and response speed in complex environments.