Dynamic Image Enhancement Algorithm in Heterogeneous Environments

doi:10.23940/ijpe.19.12.p22.32953303

Abstract

Abstract: Image acquisition in heterogeneous environments tends to lead to inadequate information and poor image quality. In order to improve the image quality of dynamic data in heterogeneous environments, an enhanced technology of dynamic data information based on Radon scale transformation is proposed. The gray histogram feature information parameters of images in heterogeneous environments are extracted. The feature quantities are fused and optimized in the central region of image clustering, and the multi-scale Retinex color feature components of dynamic data are extracted. Radon scale transformation is used to extract image centers in heterogeneous environments, enhance dynamic data of image centers, and improve image quality. The simulation results show that this method can enhance the dynamic data information of image centers in heterogeneous environments, and the output images have better imaging performance. The normalized correlation coefficient and peak signal-to-noise ratio (psnr) of the output images are higher than those of the traditional methods, which improves the peak signal-to-noise ratio (psnr) of the output image and improves the recognition performance of the image.

Key words: heterogeneous environment, image, central dynamic data, enhancement, Radon scale transformation

Xiaohong Yang and Donghong Yang. Dynamic Image Enhancement Algorithm in Heterogeneous Environments [J]. Int J Performability Eng, 2019, 15(12): 3295-3303.

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