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MicroAlgo Inc. Develops Quantum Image Edge Extraction Algorithm for Noisy Images
MicroAlgo Inc. Develops Quantum Image Edge Extraction Algorithm for Noisy Images
About this update from Microalgo, Inc.
[{"type":"text","content":"SHENZHEN, China, May 20, 2026 /PRNewswire/ -- MicroAlgo Inc. (the \"Company\" or \"MicroAlgo\") (NASDAQ: MLGO) announced today that it has proposed a quantum image edge extraction algorithm for noisy images, which is an innovative achievement of the deep integration of quantum computing and digital image processing. The algorithm takes quantum state encoding as its core, mapping the grayscale and position information of image pixels to quantum superposition states, thereby realizing parallel storage and processing of massive information.\nThe core innovation of the quantum image edge extraction algorithm for noisy images lies in the dual quantum space filter and adaptive threshold non-maximum suppression: the former constructs two correlated quantum filtering spaces to perform targeted suppression of statistical noise and impulse noise respectively, while utilizing quantum entanglement characteristics to achieve information linkage and avoid edge blurring; the latter automatically generates thresholds adapted to image features through quantum operations, enabling precise screening of edge points without manual intervention. The entire process is driven by quantum operation circuits, breaking through the efficiency and accuracy bottlenecks of classical algorithms and providing a revolutionary solution for edge extraction in complex noisy environments.Quantum State Encoding: Quantumization of Image Information The noisy image to be processed first undergoes quantum state encoding, converting the grayscale values and position coordinates of pixels into quantum superposition states. For example, the pixel values of an 8-bit grayscale image can be encoded into the superposition states of qubits, while the position information is associated with the corresponding grayscale states through quantum entanglement. This process simultaneously preserves the noise characteristics and gradient information of the image, providing a complete data foundation for subsequent processing and avoiding information loss caused by multi-step conversions in classical algorithms.Dual Quantum Space Filtering: Noise Suppression and Detail Preservation The encoded quantum image enters the dual quantum space filter. The first quantum space targets statistical noise such as Gaussian noise, suppressing noise through smoothing operations on quantum states while p...