Spatial-temporal joint zinc flotation froth image denoising based on bubble dynamic features Online publication date: Wed, 08-Jun-2022
by Wenhui Xiao; Zhaohui Tang; Jinping Liu
International Journal of Embedded Systems (IJES), Vol. 15, No. 2, 2022
Abstract: The environment of the flotation plant is harsh, and the noise pollution of the collected froth images is severe. It is challenging to obtain real-time and high-quality froth images by common denoising methods. A spatial-temporal joint denoising method based on bubble dynamic features is proposed. This method first analyses the dynamic features of the bubble and detects the stability of each reference image sub-blocks; then selects the corresponding filtering to denoising according to the different states of the froth sub-blocks; and finally obtains a weighted average result of temporal filtering and spatial filtering. This method uses a modified and noise-robust cross-correlation method to estimate the sub-blocks' motion, which improves the denoising performance of time-domain filtering. The experiments show that the method can obtain a high signal-to-noise ratio and strong structural similarity result for non-static background images. It has also been well verified in the application of zinc flotation froth images.
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