Abstract: A positioning system for precise stage is provided. It includes a designed pattern on a stage; an electron beam column generating a focused electron beam to scan the designed pattern and produce electron signal; an electron detection unit to detect the electronic signal; and a control unit converting the electron signal to a clock signal to determine the relative position of the electron beam column and the designed pattern, so as to adjust the displacement of the stage. A nanometer scale positioning method for a precise stage is provided, which can resolve the problem of mechanical drift of the stage when the stage is multi-axis positioning or rotating.

Abstract: A positioning system for precise stage is provided. It includes a designed pattern on a stage; an electron beam column generating a focused electron beam to scan the designed pattern and produce electron signal; an electron detection unit to detect the electronic signal; and a control unit converting the electron signal to a clock signal to determine the relative position of the electron beam column and the designed pattern, so as to adjust the displacement of the stage. A nanometer scale positioning method for a precise stage is provided, which can resolve the problem of mechanical drift of the stage when the stage is multi-axis positioning or rotating.

Abstract: An image reconstruction method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area; and accumulating the common area of every image. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image reconstruction.

Abstract: An image reconstruction method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area; determining a rotation centers of those images; and reconstructing three-dimensional data of those images. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image reconstruction.

Abstract: An image reconstruction method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area; determining a rotation centers of those images; and reconstructing three-dimensional data of those images. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image reconstruction.

Abstract: An image reconstruction method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area; and accumulating the common area of every image. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image reconstruction.

Abstract: An image alignment method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image alignment.

Abstract: An image alignment method includes: fetching at least two images; calculating a relative displacement between those adjacent images by utilizing a phase correlation algorithm; calculating an absolute displacement between any one of those images and the first image of those images; and computing a common area of those images by utilizing the relative displacement and the absolute displacement, then deleting remainder portions of the image excluding the common area. In the present invention, the phase correlation algorithm can be utilized to process numerous noise signals so as to get a higher precision of the image alignment.