5results about How to "Suppress blur" patented technology

This invention discloses an industrial material inspection method and system based on feature extraction and contrast enhancement, belonging to the field of image inspection technology. It includes: S1, acquiring the transmitted signal using a digital flat panel detector and generating an original digital image based on the differences in X-ray absorption by different materials or defects; S2, performing uniformity correction and normalization enhancement on the original digital image, and achieving preliminary differentiation of different material regions; S3, dividing the original image data into processing domains based on the preliminary differentiation results, and performing differentiated enhancement processing based on the local feature attributes of each processing domain to generate a binary feature image. By integrating X-ray penetration imaging, multi-dimensional image enhancement, and a deep learning-driven intelligent rating system, this invention fundamentally solves the key technical bottlenecks in traditional industrial material inspection, such as inconsistent image quality, lack of material identification, and strong subjectivity in rating, achieving an automated, intelligent, and objective upgrade in industrial material defect detection.

The invention relates to the technical field of waste liquid treatment, in particular to a self-adaptive pH amphoteric polymer-calcium salt compounded bentonite slurry rapid sedimentation treatment method. According to the method, a calcium salt working solution, a buffer working solution, an amphoteric polymer working solution and a functionalized calcium carbonate micro-powder dispersion solution are added in stages, and the stirring speed and time are accurately controlled, so that rapid sedimentation of the slurry is realized. The amphoteric polymer is formed by copolymerizing a plurality of monomers and has wide pH adaptability; the functionalized calcium carbonate micro powder is used as a weighting carrier to enhance the floc density. The method solves the problems of slow sedimentation, high supernatant turbidity and poor adaptability to water quality fluctuation in the traditional method, has the advantages of high sedimentation speed and high supernatant clarity, can be directly reused, and is suitable for bentonite slurry treatment in the fields of electric power engineering and the like.

The embodiment of the invention provides a bone microstructure parameter extraction method, computing equipment, a computer readable storage medium and a computer program product. The bone microstructure parameter extraction method comprises the following steps: firstly, carrying out super-resolution reconstruction on a CT (Computed Tomography) image to enhance the image quality; then, a first bone mask is generated through a global threshold value, a local adaptive threshold value is constructed in combination with local gray statistical characteristics, and a mask edge and a low-contrast region are subjected to reclassification to obtain a more accurate second bone mask; and then, noise connected domain elimination under volume constraint is performed on the second bone mask, and a fracture or a pseudo joint of the bone trabecula network is repaired based on morphological characteristics to obtain a high-fidelity bone tissue structure segmentation result. And finally, cortical bones are removed from the result to separate out cancellous bones, and bone microstructure parameters are extracted from the cancellous bones. According to the technical scheme provided by the embodiment of the invention, the accuracy of bone microstructure parameter extraction is improved.

This invention discloses a staring fast tracking technology based on focal plane modulation, relating to the fields of photoelectric imaging and target tracking. The technology includes: performing initialization and wide-area scanning, controlling a simulated micromirror array to scan the scene, detecting multiple targets and recording the corresponding micromirror deflection angles; performing target locking and resource allocation, dynamically allocating micromirror unit groups to each target, and driving the micromirror units to stably guide the target beam to a predetermined area of ​​the image sensor; performing focal plane modulation scanning, driving the image sensor to continuously scan along the optical axis, simultaneously acquiring multiple frames of images and generating sharpness curves for each target as the focal plane position changes; and performing multi-target image synthesis, extracting the sharp image region of each target at the optimal focal plane position, and fusing it with the global scene image to generate a panoramic sharp image. This invention enables simultaneous tracking and sharp imaging of multiple spatially discrete targets at different distances, significantly improving response speed and imaging efficiency in multi-target scenes.

The invention discloses a multi-sight-distance deep learning track line detection method based on global features, and the method comprises the steps: 1, installing a far-focus camera and a near-focus camera at the head or side surface of a train, obtaining track line images in different scenes in the train operation process, and constructing a data set; 2, in image preprocessing, a Sobel operator is used for calculating gradient energy to generate a focusing degree image, a decision diagram is generated through multi-scale morphological optimization operation, and smooth transition of fused image boundaries is achieved through Gaussian weighted fusion; step 3, constructing an improved ResNet18 backbone network, fusing multi-scale features, combining row selection and structure perception loss, and performing Adam optimization training; and 4, real-time track line detection is carried out. According to the invention, through multi-sight-distance image fusion and global feature extraction, technical support is provided for realizing high-precision and real-time detection of a train track line, automatic train driving, track state monitoring and other key tasks.