Image fusion and 3-D surface reconstruction of microparts using complex valued wavelet transforms

Microscopy imaging can not achieve both high resolution and wide image space simultaneously. Image fusion and 3-D surface reconstruction is of fundamental importance to micromanipulation in providing high lever task understanding, task planning and real time control. Purpose of image fusion is to combine those images into one single image with an extended depth-of-field. Previously, real valued wavelet transforms based image fusion suffers from shift variance, poor directionality, and lack of phase information. One promising fusion method based on complex wavelet transforms to overcome these problems is proposed. Combined 2-D position data of "in focus" pixels with a height map obtained from the proposed image fusion method, a 3-D surface reconstruction algorithm of microparts is developed. Experimental results validate performances of the proposed image fusion and 3-D surface reconstruction methods.