Quantum image edge extraction based on Laplacian operator and zero-cross method

Edge detection, as a fundamental problem in image processing and computer vision, is an indispensable task in digital image processing. Because of the sharp increase in the image data in the actual applications, real-time problem has become a limitation in classical image processing. In this paper, based on the novel enhanced quantum image representation (NEQR) of digital images, an enhanced quantum edge detection algorithm is investigated, which combines the classical Laplacian operator and zero-cross method. Because NEQR utilizes the superposition state of qubit sequence to store all the pixels of an image, the corresponding quantum image edge detection algorithm can realize parallel computation to implement the Laplacian filter and further calculate the image intensity of all the pixels according zero-cross method. The circuit complexity analysis demonstrates that our presented quantum image edge algorithm can reach a significant and exponential speedup compared to classical counterparts. Hence, our proposed quantum image edge detection algorithm would resolve the real-time problem of image edge extraction in practice image processing.