研究目的
To develop a methodological approach for creating color images in scanning electron microscopy by processing grayscale images from multiple detectors to enhance surface details on biological samples.
研究成果
The study demonstrates an effective procedure for enhancing surface details in SEM images through RGB color coding of grayscale images from multiple detectors. This approach minimizes image drift issues and combines information from different detectors to produce detailed color images, particularly useful for biological samples.
研究不足
The method requires simultaneous image recording to avoid drift, which can be challenging with non-conductive samples. Some software (e.g., Gimp) does not handle 16-bit images well, necessitating conversion to 8-bit. Beam deceleration settings for certain detector combinations were not achievable in all cases.
1：Experimental Design and Method Selection:
The study uses a scanning electron microscope with multiple detectors to simultaneously capture grayscale images, which are then merged in RGB color space using image processing software to create color images that enhance surface details.
2：Sample Selection and Data Sources:
Samples include a standard non-conductive sample (butterfly wing scales) and real microbiological samples (microbial biofilm on fiber glass filter and Bacillus subtilis cells). Samples were prepared with fixation, dehydration, critical-point drying, and sputter-coating as needed.
3：List of Experimental Equipment and Materials:
Equipment includes FEI Nova NanoSEM 450 scanning electron microscope, K850 Critical Point Dryer, Q150T ES sputter coater, aluminum stubs, silver conductive paint, glutaraldehyde, cacodylate buffer, poly-L-lysine, alcohol series, liquid CO2, platinum for coating. Software includes ImageJ, Gimp, AnalySis
4：2 Pro. Experimental Procedures and Operational Workflow:
Samples were prepared and examined in the SEM using SE, TLD, and CBS detectors at accelerating voltages from 1 to 5 kV with beam deceleration mode. Grayscale images were recorded simultaneously from different detector segments, and subsets were selected for RGB merging based on detail enhancement.
5：Data Analysis Methods:
Images were processed using ImageJ, Gimp, or AnalySis 3.2 Pro to convert and merge grayscale images into 24-bit color images, with specific RGB coding schemes applied to highlight surface features.
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