 An image detail enhancement of smart product UI interface based on stationary wavelet transformGeng Chen and Quzhi Huang International Journal of Manufacturing Technology and Management, 2024, vol. 38, issue 1, 66-80 Abstract: To overcome the problems of low image segmentation accuracy, low image signal-to-noise ratio and long image enhancement time in traditional methods, an image detail enhancement method of smart product UI interface based on stationary wavelet transform is proposed. The Gaussian mixture model is used to obtain the image parameters of the UI interface of smart products, and the image of multiple pixels is divided into marked categories by the maximum posterior probability criterion, so as to realise the segmentation of image noise area and normal area. The two-dimensional stationary wavelet transform is performed on the noisy area, and the inverse stationary wavelet transform is performed on the stationary wavelet coefficients to obtain a reconstructed image with enhanced details. Experimental results show that the image segmentation accuracy of this method fluctuates in the range of 96%-98%, the signal-to-noise ratio is 55.3 dB, and the average image enhancement time is 66.9 ms. Keywords: stationary wavelet transform; smart products; UI interface; image detail enhancement; Gaussian mixture model; image reconstruction. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmtma:v:38:y:2024:i:1:p:66-80 Access Statistics for this article More articles in International Journal of Manufacturing Technology and Management from Inderscience Enterprises Ltd |
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