Bright-field and dark-field image fusion for shape-from-focus in microscopy

Abstract

Shape-From-Focus (SFF) is a technique that can obtain 3D features of objects through monocular cameras, it can be applied with high precision in optical microscopy. However, since SFF relies heavily on the texture information of the object's surface, when the texture of some regions in the object is poor, it always leads to low accuracy or even serious errors in the depth map reconstruction of this region. Most research in SFF has focused on finding and eliminating these low-texture regions, but for the eliminated regions, how to accurately recover the depth information is not well addressed. Less attention has been paid to enriching the texture information of these regions. Considering that bright-field and dark-field light sources often present images with different textures in microscopy, this paper proposes a method to enrich image textures by fusing bright-field and dark-field images. The proposed method needs to acquire two sets of image sequences in bright field and dark field respectively, and fuse the images based on wavelet transform at the same index position in the two sets of image sequences, so that the fused images sequence can retain the high frequency components in both bright and dark field images, the fused set of image sequences is then used for SFF to calculate the depth map. Experimental results with both simulated and real objects are presented to validate the proposed schemes.