Abstract: Disclosed is a wavefront correction system based on a Runge-Kutta (RUN) optimization algorithm. The system includes a wavefront corrector, an image sensor, a lens, a computer control module, an image collection card, a digital-to-analog (D/A) converter, and a high-voltage amplifier. A performance index function representing a wavefront distortion correction degree is used as an optimization algorithm objective function, a RUN algorithm is used as a closed-loop correction system control algorithm, and the wavefront corrector is used as a wavefront distortion correction system device. The RUN algorithm controls the wavefront corrector to correct a wavefront aberration. During each iteration, a voltage control signal obtained through the algorithm is amplified and applied to the wavefront corrector, such that a mirror shape of the wavefront corrector is changed, and a corresponding corrected wavefront is generated.

Abstract: A method is provided for recognition of a sky portion, a vertical object portion and a ground portion in an image. The image into a plurality of pixel sets by the electronic system. Expected values of each pixel sets with a sky distribution function, a vertical object distribution function and a ground distribution function by the electronic system are calculated and compared for each pixel set for determine each pixel set belonging to one of the sky portion, the vertical object portion or the ground portion.

Abstract: A method is provided for classifying pixels in an image into super pixels that may be executed in one or more than one electronic devices. Seed pixels are pixels selected from the image. Color distances of a color space similar to human vision perception between the seed pixels and proximal pixels are calculated. The proximal pixels are pixels located proximally to corresponding seed pixels. Geographic distances are also computed for two pixels and the geographic distances are combined with the color distances as a reference for classifying pixels into super pixels.