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Focus variation measurement (FVM), an optical contact-free method, has deep scientific research and application value for precision engineering, micro-manufacturing, quality inspection, biotechnology, clinical medicine and other fields. In order to reproduce a large-scale 3D surface micro topography and to realize the automatic measurement of the characteristic parameters of an object. The 3D model construction and mosaic (stitching) algorithm are excavated and studied based on 2D multifocus image sequence. In the research of 3D model reconstruction, a better focus measure is proposed based on the sum of the modified Laplacian (SML), which considers the relationship between the pixel and its diagonal direction pixels. And the 3D reconstruction models mosaic are guided by the mosaic of the 2D fused images for the reason that the pixels of the 2D fused image correspond to the depth points of the 3D reconstruction model. In order to verify the feasibility of the above methods, a comparative experiment is conducted on the standard triangular block model reconstruction with the SML and the proposed algorithm, which verifies the superiority of the proposed algorithm. Then, the two 3D models of the standard triangular block with overlapping parts are stitched and extracted the angle value. By comparing with the standard values, these angle values of 3D stitched model are within the standard value range, which verifies the feasibility of the stitching algorithm.

In the multifocus microscopic image measurement method, the distortion of the three-dimensional (3D) reconstruction model has always been an important factor affecting the measurement result. In spatial domains, the focus measure algorithm is based on the gradient change of the pixel point to determine the degree of focus of the pixel. So it will be difficult to accurately extract the focus of the pixel in the areas where color difference is not obvious, resulting in 3D model distortion. According to the optical principle, the high-frequency coefficients of the clear image are larger than the high-frequency coefficients of the blurred image. Based on this characteristic, this paper proposes a new multifocus microscopic image 3D reconstruction algorithm using a nonsubsampled wavelet transform (NSWT). The NSWT does not consider the downsampling in wavelet decomposition and has translational invariance. Therefore, the wavelet transform value of each pixel can be calculated in the image, so the high-frequency coefficient of each pixel can be obtained; then the convolution calculation is performed on the high-frequency coefficients of the pixel points in the fixed window as the focus measure value of the pixel point. Compared with the traditional algorithm, the algorithm proposed in this paper can show better unimodal and antinoise performance on the focusing measure curve. In this paper, the reconstruction of the experimental object is Alicona standard block triangular and semicylindrical. The proposed algorithm and the traditional algorithm for comprehensive measure use the root mean square error, peak signal to noise ratio, and correlation coefficient as the measure index. The experimental results and comparative analysis prove the correctness of the proposed algorithm and enable more accurate reconstruction of 3D models based on multifocus microscopic images.

Some meaningful achievements have been made on the solubilities of inorganic salts and organic compounds in sub- and supercritical water. But the solubility data remain too scarce to meet the need of modern industry due to the harsh of experimental conditions,equipment requirements and experimental operations,which greatly affects the research and development processes of sub- and supercritical fluid technology in chemical synthesis,extraction and separation,environmental engineering and many other fields. Basic researches still need to be carried out to determine the solubility data and its influence factors of substances in sub- and supercritical water. This paper reviews the research advances of inorganic salts and organic compounds solubility in sub- and supercritical water. The developments of the solubilities of inorganic salts and organic compounds in sub- and supercritical water in fused silica capillary reactor,instead of the traditional stainless steel autoclave or tubular flow reactor,combined with microscopic observation,heating-cooling stage,real-time digital video and in-situ Raman designed by author's group are highlighted in this paper.

Depth from focus (DFF) is a technique for estimating the depth and three-dimensional (3D) shape of an object from a multi-focus image sequence. At present, focus evaluation algorithms based on DFF technology will always cause inaccuracies in deep map recovery from image focus. There are two main reasons behind this issue. The first is that the window size of the focus evaluation operator has been fixed. Therefore, for some pixels, enough neighbor information cannot be covered in a fixed window and is easily disturbed by noise, which results in distortion of the model. For other pixels, the fixed window is too large, which increases the computational burden. The second is the level of difficulty to get the full focus pixels, even though the focus evaluation calculation in the actual calculation process has been completed. In order to overcome these problems, an adaptive window iteration algorithm is proposed to enhance image focus for accurate depth estimation. This algorithm will automatically adjust the window size based on gray differences in a window that aims to solve the fixed window problem. Besides that, it will also iterate evaluation values to enhance the focus evaluation of each pixel. Comparative analysis of the evaluation indicators and model quality has shown the effectiveness of the proposed adaptive window iteration algorithm.