本文關(guān)鍵詞： 煤礦圖像 負片修正 塵霧清晰化 光環(huán)效應(yīng) 去霧　出處：《煤礦安全》2017年09期 　論文類型：期刊論文

【摘要】：由于煤礦井下環(huán)境惡劣,存在大量的粉塵、水霧,使得煤礦井下視頻監(jiān)控獲取的圖像嚴重降質(zhì),而現(xiàn)有的基于暗通道先驗的塵霧清晰化算法在處理煤礦塵霧圖像時存在局限性,因此提出了一種改進的基于負片修正的塵霧圖像清晰化算法。針對原有算法產(chǎn)生的嚴重的光環(huán)效應(yīng),通過建立參數(shù)間的映射實現(xiàn)了修正參數(shù)的精細化,從而有效的抑制了光環(huán)效應(yīng)的產(chǎn)生。考慮獲取的復(fù)原圖像亮度比較低,對其進行伽馬校正并獲得最終清晰化圖像。與其他算法相比,該算法能夠有效的對塵霧圖像進行清晰化復(fù)原,使得復(fù)原圖像色彩更加飽和、信息量更加豐富,展現(xiàn)了該算法的優(yōu)越性。
[Abstract]:Due to the harsh environment in the underground coal mine, there is a large amount of dust and water mist, which makes the image obtained by the video monitoring in the coal mine seriously degraded. However, the existing dust-fog clarity algorithms based on the dark channel priori have some limitations in dealing with the dust fog images in coal mines. Therefore, an improved dust image clarity algorithm based on negative correction is proposed. Aiming at the serious halo effect produced by the original algorithm, the refined parameters are refined by establishing the mapping between the parameters. Thus the halo effect is effectively suppressed. The reconstructed image is considered to have lower brightness, and the gamma correction is carried out and the final clear image is obtained. Compared with other algorithms. The algorithm can effectively restore the dust-fog image clearly, make the restored image more saturated color, more rich information, showing the superiority of the algorithm.
【作者單位】： 北京大學(xué)地球與空間科學(xué)學(xué)院;
【基金】：國家重點研發(fā)計劃重點專項資助項目(2016YFC0801807,2016YFC0801805)
【分類號】：TD714;TP391.41
【正文快照】： 視頻監(jiān)控在煤礦安全生產(chǎn)中扮演著重要的角色,它能夠?qū)⒕伦鳂I(yè)信息通過圖像的方式及時反饋給生產(chǎn)指揮者,從而指導(dǎo)井下生產(chǎn)有序進行并及時處置井下危險情況。然而由于煤礦井下環(huán)境惡劣,在煤礦生產(chǎn)中有大量粉塵產(chǎn)生,同時井下除塵裝置也會產(chǎn)生的大量水霧,使得監(jiān)控視頻獲取的圖像，

本文編號：1459796