Adaptive Enhancement of Robot Vision Image on the basis of Multi-Scale Filter

Authors

  • Xin Liu School of Electronic Information Engineering, Lanzhou Institute of Technology, Lanzhou 730030, China
  • Bin Zhang Gansu Radio Management Committee Office, Lanzhou 730030, China

Abstract

To improve the image quality effectively, increase the mean square error value, information entropy and average gradient, an adaptive enhancement method for robot vision images is proposed based on multi-scale filters. An HSV color space model is built in order to: enhance the brightness and saturation components of the image; smooth the robot vision image through the total variation model and remove the noise in the image. The compressed sensing reconstruction algorithm is used to reconstruct the robot vision image and to improve the real-time and rapid processing of the image. The multi-scale filter obtained by the combination of the multi-scale Gaussian filter (MGF) and the high-pass filter (HPF) improves the adaptive processing of the robot vision image, and enhances the image by adjusting the weight of each filter. The experimental results show that the proposed method has a higher mean square error value, information entropy and average gradient, better image visual effect, and the enhanced image has sharp details and moderate color.

Keywords: multi-scale filter; image enhancement; HSV color model; compressed sensing; mean square error; average gradient

Cite As

X. Liu, B. Zhang, "Adaptive Enhancement of Robot Vision Image on the basis of Multi-Scale Filter", 
Engineering Intelligent Systems, vol. 30 no. 4, pp. 255-263, 2023.





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Published

2023-07-01

Issue

Vol. 31 No. 4 (2023): International Journal of Engineering Intelligent Systems

Section

Article

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