38results about How to "Achieve super resolution" patented technology

The invention discloses an image super-resolution reconstruction method based on dictionary learning and structure similarity, mainly solving the problem that a reconstructed image based on the prior art has a fuzzy surface and a serious marginal sawtooth phenomenon. The image super-resolution reconstruction method comprises the following implementation steps of: (1) acquiring a training sample pair; (2) learning a pair of high / low-resolution dictionaries by using structural similarity (SSIM) and K-SVD (K-Singular Value Decomposition) methods; (3) working out a sparse expression coefficient of an input low-resolution image block; (4) reestablishing a high-resolution image block Xi by using the high-resolution dictionaries and the sparse coefficient; (5) fusing the high-resolution image block Xi to obtain a high-resolution image X'I subjected to information fusion; (6) obtaining a high-resolution image X according to the high-resolution image X'I; and (7) carrying out high-frequency information enhancement on the high-resolution image X through error compensation to obtain a high-resolution image subjected to high-frequency information enhancement. A simulation experiment shows that the image super-resolution reconstruction method has the advantages of clear image surface and sharpened margin and can be used for image identification and target classification.

The invention relates to a phase-staggered super-resolution method for respiratory motion signals on the surface of the chest and abdomen, which belongs to the technical field of precision instruments and thoracoabdominal radiotherapy; the method first converts the respiratory motion signal into a periodic signal through a signal conversion module, and then through a phase difference multi-output module , forming three outputs with equal phase difference with a phase difference of π / 2, and then forming five outputs with equal phase difference with a phase difference of π / 5 through the resistance chain multiphase generating module, and then forming a square wave through a multiphase sine square wave conversion module, And through the multi-phase fusion logic gate module to form the out-of-phase super-resolution square wave output, that is, to realize the transformation of one cycle of respiratory motion signal into a multi-cycle out-of-phase square wave signal, and the phase error phase super-resolution square wave output signal quarter cycle of .

The invention discloses a structure illumination super-resolution microscopy imaging system and an imaging method thereof. The imaging system comprises an illumination light source, a rotating structure light generator, a first convergent lens, a light splitter, an objective lens, an object stage, a sample, a second convergent lens, a digital imaging device and a computer. An original image is processed through an imaging image reconstruction algorithm; super-resolution can be achieved only by rotating structured light stripes for four times without phase displacement; the imaging image reconstruction algorithm is based on frequency domain processing instead of non-spatial domain processing; a spectrum process of a super-resolution image of a sample is different from a traditional frequency domain method, structured light directions are not analyzed one by one and all directions are merged for analysis; in order to obtain traditional uniform 2-fold resolution improvement in various directions, the theoretical quantity of original images can be reduced to 4 from 9 of a traditional method; the quantity of the original images is further reduced to 3 and uniform 1.5fold resolution improvement in various direction can be theoretically obtained.

The invention relates to a multiphoton subpulse STED-SPIM (Selective Plane Illumination Microscopy) microscopic system realized by single wavelength, characterized in that the femtosecond pulse laser emitted by a femtosecond single wavelength laser is transmitted to a first splitter through a first polarization regulator to be divided into two beams of light, and a first beam of light is successively transmitted to a second polarization regulator, a second splitter, a third polarization regulator and a quarter-wave plate along a Y-axial direction to form an excitation light beam; a second beam of light is transmitted to an STED photoquenching system, and the light outputted by the STED photoquenching system is successively emitted into the second splitter, the third polarization regulator and the quarter-wave plate to be modulated into donut-shaped focus spots to form a quenching light beam; a scanner is used for scanning the excitation light beam and the quenching light beam to generate an excitation plate light source and an STED quenching plate light source; an excitation plate light source and an STED quenching plate irradiate an object to be imaged through an excitation objective lens to allow the flourescent dye of the object to be imaged to excite fluorescence, and excited fluorescence is imaged through an imaging objective lens, and is emitted to a photosensitive element or an analysis element successively through an optical filter and a convergent lens.

The invention discloses a graph-model-based single image super-resolution output method. The graph-model-based single image super-resolution output method includes the following steps: 1) according toa preset sampling rate, performing interpolation on an input single image by means of a bicubic interpolation method, obtaining a low resolution image, segmenting the obtained low resolution image into m*n image blocks, calculating the Euclidean distance of the pixel value of each image block, and according to the Euclidean distance, determining a set of similar blocks, wherein each image block in the segmented low resolution image has one set of similar blocks; 2) constructing a graph model for the set of similar blocks; 3) performing Laplace transformation on the obtained two dimensional matrix to obtain a Laplace matrix, and then carrying out restoration of the image blocks through solution by means of an optimization formula; and 4) averaging and reconstructing the restored image block set, and finally obtaining a super-resolution image. The graph-model-based single image super-resolution output method can overcome the defect that a machine learning method needs mass image data totrain a model, thus being more suitable for image super resolution.

This invention discloses a new usage of photochromic diarylethenes compound, in which, the inventer verifies from experiments that the near field super resolution optical storage CD with photochromic diarylethenes compound as the mask layer has the advantages of high density and small size in recording information.

The method for super-resolution of respiratory motion signals on the surface of the chest and abdomen of the present invention belongs to the technical field of precision instruments and radiotherapy of the chest and abdomen; the method first converts the respiratory motion signal into a periodic signal through a signal conversion module, and then uses a phase difference multi-output module to form a phase difference Three outputs with equal phase difference of π / 2, and then through the resistance chain multi-phase generation module to form five outputs with equal phase difference of π / 5, and then through the multi-phase sine square wave conversion module to form a square wave, and through the multi-phase The fusion logic gate module forms a quasi-phase super-resolution square wave output, which realizes the transformation of one cycle of the respiratory motion signal into a multiple-cycle quasi-phase square wave signal, and the phase difference is zero cycle of the quasi-phase super-resolution square wave output signal.