6 results about "Reduced contrast volume" patented technology

The application is an underwater image super-resolution reconstruction method based on dynamic window and state space cooperation. The method comprises a shallow feature extraction module, a deep feature extraction module and an image reconstruction module, through the construction of a double-path feature interaction mechanism, the alternative learning of a dynamic window attention module and a visual state space module is adopted, the cooperative optimization of local detail enhancement and global context modeling is realized. A dynamic channel gate feedforward network is innovatively designed, through a channel weight dynamic adjustment mechanism guided by a global average pooling, adaptive fusion of multi-scale features is realized. The method effectively solves the problems of blur and contrast reduction of underwater images caused by scattering effect, the PSNR is 28.21dB in the x3 task of the USR-248 dataset, which is 0.35dB higher than that of SRFormer, the experimental results show that the model has excellent performance in objective evaluation index and subjective evaluation, and remarkable effect is achieved in detail recovery, which has significant technical effect and industrial application value.

The application discloses a low-light enhancement method and device based on a dynamic filter and a storage medium, and belongs to the technical field of image processing. The low-light enhancement method based on the dynamic filter first extracts different scale features of an input low-light image by using a residual down-sampling module and a pyramid convolution pooling module in an encoder to obtain multi-scale image feature information; then, the feature information of different scales is input into a filter generation network to obtain each local dynamic filter at a decoding end, and the image feature information obtained by the encoder is input into a decoder to perform decoding processing by using each local dynamic filter and a pixel recombination up-sampling module, so that low-light enhancement and blur removal are realized. The method has the characteristics of multi-scale feature extraction, feature enhancement, spatial change adaptability and structure reservation, and solves the problem that insufficient light greatly reduces the visual quality of an image, and further causes image detail blur, contrast reduction and noise.

This invention discloses an anti-glare floating object detection method based on deep learning and image enhancement. To address the issues of strong reflections and local overexposure caused by direct sunlight in water surface monitoring scenarios such as rivers and reservoirs, leading to reduced contrast and missed detections of floating objects, as well as the problems of numerous false targets and unstable detection results caused by dynamic backgrounds such as water ripples, waves, and currents, this invention decomposes water surface image sequences into specular and diffuse reflection components to generate glare and overexposure masks. A diffusion repair network is used to repair and reconstruct overexposed areas of the diffuse reflection component. During instance segmentation, multi-scale features are weighted and suppressed based on the glare mask to reduce glare interference. Furthermore, a temporal mask propagation network is employed for cross-frame propagation and consistency correction, outputting the floating object instance outline and confidence level. This achieves improved detection accuracy, reduced false detections, and continuous and stable results for floating objects under strong glare and dynamic backgrounds.

The application provides a kind of microscopic imaging method and probe device based on laser illumination, belong to microscopic imaging technical field, the present application is generated laser by semiconductor laser and is conducted to lens system by optical fiber and forms transmission type illumination, utilizes rotation diffusion sheet and carries out speckle time domain average processing to reduce speckle contrast to threshold value below, adopts pulsed laser stroboscopic illumination mode to eliminate motion blur, by telecentric lens and industrial camera collection through the groove in the particle image, with high density particle adhesion segmentation processing based on graph cut accurately separates adhesion particle from high solid content image and extracts particle shape parameter and particle size distribution data, finally by laser power self-adaptive regulation and control artificial intelligence model, according to image quality evaluation function, realize illumination power closed loop control, solve the technical problem that particle adhesion segmentation precision is seriously reduced under high solid content scene caused by laser speckle noise.

The application provides a shielding film defect detection method and system, the method comprising: acquiring a transmission image, a red light reflection image and a near-infrared reflection image corresponding to the shielding film, and then acquiring a defect feature image; filtering out frequency domain components corresponding to inherent periodic textures of the shielding film in the defect feature image to obtain an enhanced image; inputting the enhanced image into a feature extraction network to obtain a defect feature map; obtaining a defect feature vector based on the defect feature map, comparing the defect feature vector with a plurality of defect feature templates, and obtaining a detection defect category. By acquiring images of three different physical imaging modalities of transmission, red light reflection and near-infrared reflection, the information limitation of single waveband imaging is broken, the signal-to-noise ratio and detectability of the defect signal are improved from the source, the contrast is improved, and the missed detection rate is reduced. By filtering out the inherent periodic textures of the shielding film, the background texture interference is targeted and actively suppressed, and the probability of misjudging the texture as a defect is reduced.