The invention discloses a different resolution infrared and visible light image fusion method and system based on total variation, which comprises establishing a total variation model of image fusion,respectively constraining the fusion image and the infrared image with a data fidelity term and a regularization term, and fusing the relationship between the image and the visible light image, according to the source image, solving the optimal solution of the total variational model and obtaining the fusion result. The invention builds a model according to the situation that the original infrared image and the visible image have different resolutions, and the obtained fusion image has high resolution and clear texture details, while retaining the characteristic that the pixel intensity distribution of the infrared image protrudes out of the thermal target, and the fusion result is convenient for human eyes to discriminate the thermal target and has good visual effect.

Different resolution infrared and visible light image fusion method and system based on total variation

The invention provides a method and device for measuring a fetal head circumference in an ultrasound image. The method comprises the steps that the position of a longest edge line in the ultrasound image is obtained, and a specified area is searched for according to the position; whether or not the designated area is successfully searched for is judged; if yes, search results are combined in a specified manner to obtain a fetal head circumference area, and the fetal head circumference is calculated according to the fetal head circumference area. The method and device for measuring the fetal head circumference in the ultrasound image have the advantages that the situation can be avoided that the whole image area is searched for by sliding a window when fetal head position is automatically positioned by taking the position of the longest edge line as a search starting position, thereby improving the search efficiency, and positioning of the head circumference area can be performed through a second area identification method when searching for the head circumference area fails, thereby avoiding manual operation and facilitating diagnosis by a clinician.

Method and device for measuring fetal head circumference in ultrasound image

The invention relates to a method of rebuilding an under-sampled image based on a minimal second-order total generalized variation. The method comprises the following steps: (1) calculating a second-order total generalized variation of the under-sampled image; (2) obtaining a minimal value of a TGV norm through a conjugate gradient method; and (3) carrying out rectangular projection and error correction processing on each iteration result, so as to obtain an applicable parameter integration used for image rebuilding. The method provided by the invention can obtain a more accurate rebuilding result.

Method of rebuilding under-sampled image based on minimal second-order total generalized variation

The invention discloses a high-definition image reconstruction method for a photoacoustic microscope based on second order total generalized variation, and the method comprises the steps: S1, obtaining a low-definition image of the photoacoustic microscope; S2, carrying out the interpolation of the low-definition image of the photoacoustic microscope and obtaining a interpolation image; S3, determining an optimization model for optimizing the interpolation image based on the second order total generalized variation; S4, reconstructing the high-definition image of the photoacoustic microscope through employing a convex optimization algorithm based on the optimization model According to the invention, the second order total generalized variation serves as a bound term, and the optimization algorithm is combined, so the high-definition image of the photoacoustic microscope is reconstructed through the low-definition image of the photoacoustic microscope, thereby enabling the detail of the image to be clearer The method achieves the reconstruction of the high-definition image of the photoacoustic microscope through the image processing of the low-definition image of the photoacoustic microscope, so the method does not need to increase any system cost for obtaining the high-definition image

High-definition image reconstruction method for photoacoustic microscope based on second order total generalized variation

The invention discloses an image super-resolution reconstruction method based on a DOG operator. The method includes: a DOG image D corresponding to an input low-resolution image Y is solved, and a DOG absolute value is maximized; a constrained maximization problem of the DOG absolute value is changed into an unconstrained minimization problem by employing a Lagrange multiplier method, the unconstrained minimization problem is handled by employing a gradient descent method, a value X is obtained after processing, and the X refers to the high-resolution image.

Image super-resolution reconstruction method based DOG operator

The invention discloses a total generalized variation-based infrared image multi-sensor super-resolution reconstruction method The total generalized variation-based infrared image multi-sensor super-resolution reconstruction method mainly comprises the steps of projecting a low-resolution infrared image into the coordinate space of a high-resolution visible image, obtaining a sparse infrared image and solving a data item weighting coefficient according to the sparse infrared image; performing normalization processing on the sparse infrared image and obtaining a normalization infrared image; solving the marginal information of the high-resolution visible image through a phase equalization algorithm; constructing a data item by the data item weighting coefficient and the normalization infrared image; weighting a TGV regular term improved by a first-order gradient operator through the marginal information of the visible image and constructing a regular bound term; adding the data item and the regular bound term to construct an objective function, solving the objective function in an iterative mode through a primal-dual optimization algorithm with the normalization infrared image serving as an initial value and obtaining a reconstructed high-resolution infrared image Experiments show that the quality of the image reconstructed by the total generalized variation-based infrared image multi-sensor super-resolution reconstruction method is high and the image is close to an original high-resolution infrared image

Total generalized variation-based infrared image multi-sensor super-resolution reconstruction method

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Total generalized variation-based infrared image multi-sensor super-resolution reconstruction method