4results about How to "Eliminate blocking" patented technology

The invention belongs to the technical field of remote sensing image processing, provides a remote sensing image blocking effect elimination method fusing adaptive weight and an anchoring mechanism, and aims to eliminate the blocking effect from a global level, take radiation consistency as a constraint condition, introduce the adaptive weight to carry out differential adjustment on constraint intensity of different overlapped regions, and improve the blocking effect elimination efficiency. Meanwhile, an anchoring mechanism is adopted, stabilization constraint is carried out on an overall solution space, finally, a global equation set is constructed, an iterative least square optimization strategy is used for solving, image radiation consistency and visual continuity are integrally ensured, and the quality of remote sensing images is improved.

The application discloses a kind of image shadow removal methods of balancing deterministic recovery and perceived quality, comprising:1, first stage global regression analysis is carried out to shadow image, global illumination and color consistency of image are repaired using global regression network based on no residual, and deterministic illumination anchor point is established;2, the output of global regression network is input into the diffusion model of second stage as conditional space prior, and local perceptual refinement is carried out using conditional diffusion model based on block, and fine texture details are recovered by generative prior;3, in the reverse denoising sampling process of second stage, introduce random block overlap mechanism, calculate the mean of all covering block prediction noise as updating basis for the purpose of eliminating the boundary artifact when full resolution inference.The application can significantly improve the visual fidelity of the de-shadowed image while ensuring pixel-level accuracy, and can efficiently process high-resolution images under limited video memory constraints.

The application discloses a high-density NAND storage medium adaptive repair method, which comprises the following steps: a master control chip separates a target feature vector representing a real aging trend of a storage unit from original read data containing random physical noise; the master control chip deduces the target feature vector by using a full integer recursive prediction model to obtain a health state prediction result of the storage unit in a future preset time period; wherein the health state prediction result comprises a best read reference voltage offset and an estimated bit error rate growth curve; and the master control chip adjusts the charge distribution form and the programming voltage parameter of data on the storage unit in the data writing stage according to the health state prediction result. In the above manner, the firmware pipeline blockage and performance jitter problems caused by floating point operation and large model parameter loading can be eliminated in a restricted hardware environment where the master control chip only supports integer operation and the on-chip cache is extremely small.

The invention discloses a real-time image enhancement method and system based on CD-SEM raster scanning partitioning, and the method comprises the steps: S1, controlling an electron beam of a CD-SEM to scan a to-be-detected region according to a raster scanning path based on a preset image processing block size and overlapping region parameters, and obtaining an image collection block; s2, acquiring an image acquisition block, performing local histogram statistics, cutting and equalization processing on the current image acquisition block in sequence, generating a corresponding enhanced image processing block, and outputting the enhanced image processing block; s3, splicing the current image processing block with the spliced image; non-overlapped pixels between the current image processing block and the adjacent spliced image processing block are directly spliced; and for the pixels in the overlapped region, gray fusion is carried out by adopting a weighted average algorithm, so that a final overall enhanced image is generated. The method has the advantages of high efficiency, low delay, low memory occupancy, seamless integration, excellent enhancement effect and the like.