Research On Edge Detection Scheme Design Of Quantum Image

Edge detection is a fundamental issue in image processing that plays a crucial role in face recognition,medical imaging,satellite images,and other related fields.While classical image edge detection algorithms have been relatively mature,there are few reports on quantum image edge detection.This paper addresses this gap by designing the classical Marr-Hildreth edge detection algorithm and the quantum circuit of classical Canny edge detection in the quantum computing paradigm,based on the research progress of quantum image edge detection at home and abroad.We propose a novel method for realizing Marr-Hildreth edge detection in quantum images by designing quantum circuits of Gaussian filtering and Zero-Crossing extraction.The Gaussian filtering is achieved through quantum adders and multipliers,while the Zero-Crossing extraction is accomplished through quantum comparators and auxiliary modules.Simulation experiments demonstrate that the scheme is more robust compared to previous schemes when quantum noise is added.To achieve better edge detection results,we further study the specific implementation of the Canny detector in the quantum computing paradigm.For Gaussian smoothing filtering and Sobel sharpening operators,we propose a new method,called “Translation,S-tacking and Weighted Summation,” which fully utilizes the parallelism of quantum computing to accelerate its classical counterpart and avoid convolution operation.To calculate the gradient and angle required for edge detection,we introduce the binary complement description of gray-scale value and design new operators such as addition,multiplication,and division of signed numbers.For non-maximum suppression and double threshold processing required for edge detection,we design separate quantum circuits that implement these tasks by introducing quantum complement comparators.Complexity analysis shows that the quantum Canny edge detector has exponential speedup compared to its classical counterpart.Simulation experiments on a classical computer demonstrate the feasibility and effectiveness of the scheme,revealing that the research idea of integrating quantum computing and image processing is feasible.