Research Of Defouces Microscopy Image 3-D Surface Reconstruction

Micro stereovision based on stereo light microscope (SLM) is used insome Micro-domains such as micromanipulation, microassembly, etc.There are mainly two purposes of micro stereovision: the first is that it isused to auto position in micromanipulation and microassembly by thevision feedback and helps the mechanical hand to complete-the expectedoperation; the second is that it contains the 3D depth information which isused in the measurement of 3D attributes. In this paper, some importantissues correspondent with micro stereovision based on SLM are studied forsolving problems of micro positioning and micro measurement, such as themathematical description of the imaging process of SLM, the imagepreviously treatment, the image matching algorithm and a depth estimationalgorithm interpolates a small number of focus measure values to obtainaccurate depth estimates etc. Results derived from this paper can be used to3D measurements of objects with a small scale and 3D positioning inmicromanipulation, and microassembly.The main content of this paper is reconstructs the object surface to 3Dsurface use one-eye microscope. We can't obtain the clear and allinformation from one image because of the limitation of the microscopicfocal length. We displace the object in the Z axial so we can obtain a sequence of object images, then we pick-up the focus area in every imageand fusion them in a image. The sum-modified-Laplacian (SML) operatoris developed to provide local measures of the quality of image focus. Adepth estimation algorithm interpolates a small number of focus measurevalues to obtain accurate depth estimates information to reconstruct theobject surface to 3D surface.Firstly, the paper adopts the edge characteristic image registration, andthe practical experiments prove this auto-matching method is effective.Secondly, the research analyses the principle of image decomposition andreconstruction based on wavelet-pyramid method. From the former way thepaper proposes a new wavelet transform algorithm based on the energyfusion rules. And the new way can remove the defocused areas showed bythe experimental result. And through the entropy and others evaluation, thecomprehensive evaluation result was achieved. Thirdly, in order to obtain3D structures of the object to reconstruction the object surface to 3D image,Gaussian interpolation algorithm has been selected to interpolate a smallnumber of focus measure values to obtain accurate depth estimates.Based on the different energy distributions of the low-frequencyband and the high-frequency band, which are achieved by discrete waveletstransform, an original method for wavelet coefficient combination isproposed in this paper. It takes the ratio of the two bands as a characteristicvalue and the maximum value is chosen as an integration rule for determining new wavelet coefficients. This method can remove thedefocused areas and reduce the distortion of the fused images. Finally, theadvantage of the proposed fusion approach is demonstrated clearly bypractical experiments, by comparison with conventional area based pixelselection method. Because of the characteristic of acquire images use onesensor, Gaussian interpolation algorithm has been selected to interpolate asmall number of focus measure values to obtain accurate depth estimates to3D reconstruction.