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The images were analyzed by image processing software for detecting the liquid-squeezed area based on a circle detection algorithm as described in the flowchart of Fig. 4a.
The percentage of signal fluorescence per photographed field was analyzed by image processing software (Image Pro-Plus, MediaCybernetics, Inc., Silver Spring, MD).
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The pictures were analyzed by image processing using 2 arbitrarily chosen thresholding levels.
Pictures from the multiple cameras are then stitched together by image processing software on a computer connected to the sphere, creating one highly detailed image.
The images were optimized for best contrast and brightness by image processing software (Adobe Photoshop v. 7.0).
Images of the specimen surfaces were obtained by scanning electron microscopy (SEM) and analyzed by specific image processing software (SPIP™ - 3D Image Processing).
They were analyzed by the image processing software Image J versionn 1.45) to obtain a group of data sets including (i) size measured by 'Area' and (ii) shape measured by 'Width', 'Height', and 'Circularity' of the chloroplast and starch granule cross-sections.
The sphere size distribution and morphology was analyzed using image processing software on SEM pictures.
A 3D laser scanner was used as a measurement device and the 3D images were analyzed using image processing software.
The images were converted to black and white in image processing software Picasa version 3.9.16.37 and analyzed in image processing software ImageJ version 1.47 (Abramoff et al. 2004).
Digital images were obtained using a Leica SCN400 system, and the H&E or immunofluorescently stained specimens were analyzed using IP Lab image processing software, as described earlier 30.
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