本文選題：圖像去霧　切入點(diǎn)：暗原色先驗(yàn)　出處：《中國圖象圖形學(xué)報(bào)》2017年06期 　論文類型：期刊論文

【摘要】：目的針對(duì)暗原色先驗(yàn)原理對(duì)霧霾圖像中天空或白色物體等明亮區(qū)域透射率估計(jì)不足,導(dǎo)致該區(qū)域去霧后彩色失真的問題,提出一種基于暗原色先驗(yàn)和引導(dǎo)濾波修正大氣耗散函數(shù)的單幅圖像去霧算法。方法首先,基于暗原色先驗(yàn)?zāi)Ｐ偷玫酱髿夂纳⒑瘮?shù)的粗估計(jì)值;其次,構(gòu)造一個(gè)修正函數(shù),糾正暗先驗(yàn)失效的明亮區(qū)域的大氣耗散函數(shù);然后,對(duì)修正后的大氣耗散函數(shù)和求得的初始傳輸圖分別利用引導(dǎo)濾波進(jìn)行優(yōu)化,平滑圖像邊緣的同時(shí)保持圖像細(xì)節(jié)信息;最后,由優(yōu)化后的傳輸圖和估計(jì)的大氣光值得到復(fù)原圖像。結(jié)果選取多幅經(jīng)典圖像進(jìn)行對(duì)比實(shí)驗(yàn),并利用峰值信噪比和均方誤差衡量去霧結(jié)果的失真程度。實(shí)驗(yàn)結(jié)果表明,本文算法不但在非明亮區(qū)域可以得到較好的去霧效果,而且也能使圖像中的明亮區(qū)域保持原有色彩,相比而言本文算法得到的復(fù)原圖像整體失真較少;對(duì)于大小為460×300像素的圖像,本文算法與He方法相比,得到的復(fù)原圖像峰值信噪比提高了0.600 5 d B,均方誤差降低了0.002 6,耗時(shí)縮短了29.622 0 s。結(jié)論對(duì)于霧天包含明亮區(qū)域的降質(zhì)圖像,提出了一種修正大氣耗散函數(shù)的單幅圖像去霧算法。實(shí)驗(yàn)結(jié)果的主觀和客觀評(píng)價(jià)表明本文算法對(duì)天空或白色物體等明亮區(qū)域能得到較好的去霧效果,有效改善了暗原色先驗(yàn)原理對(duì)圖像中明亮區(qū)域造成的彩色失真問題。
[Abstract]:Aim to solve the problem of color distortion caused by dark priori principle in haze image due to insufficient estimation of the transmittance of bright regions such as sky or white objects. This paper presents a single image de-fogging algorithm based on a dark priori and a guided filter to modify the atmospheric dissipation function. Firstly, based on the dark priori model, the coarse estimation of the atmospheric dissipation function is obtained; secondly, a correction function is constructed. The atmospheric dissipation function of the bright region with dark prior failure is corrected. Then, the modified atmospheric dissipation function and the obtained initial transmission diagram are optimized by guided filtering, respectively, to smooth the image edges while keeping the image details. From the optimized transmission map and the estimated atmospheric light, the reconstructed image is worth recovering. Results A number of classical images are selected for comparison experiments, and the distortion degree of the de-fogging result is measured by using the peak signal-to-noise ratio (PSNR) and mean square error. The experimental results show that, This algorithm can not only get better effect in the non-bright region, but also keep the original color in the bright region of the image, compared with the whole distortion of the restored image obtained by the algorithm in this paper. For an image of 460 脳 300 pixels, the peak signal-to-noise ratio (PSNR) of the reconstructed image is increased by 0.600 5 dB, the mean square error is reduced by 0.002 6, and the time is shortened by 29.6220 s compared with that of he method. Conclusion for the degraded image with bright region in fog, the mean square error is reduced by 0.002 6, and the mean square error is reduced by 29.6220 s. A single image de-fogging algorithm with modified atmospheric dissipation function is proposed. The subjective and objective evaluation of the experimental results show that the proposed algorithm can achieve better defog effect for bright regions such as sky or white objects. The color distortion caused by the priori principle of dark primary color in the bright region of the image is effectively improved.
【作者單位】： 西北大學(xué)信息科學(xué)與技術(shù)學(xué)院;洛陽師范學(xué)院中原經(jīng)濟(jì)區(qū)智慧旅游河南省協(xié)同創(chuàng)新中心;
【基金】：國家自然科學(xué)基金項(xiàng)目(61502219) 中國博士后科學(xué)基金項(xiàng)目(2015M582697) 國家科技支撐計(jì)劃基金項(xiàng)目(2013BAH49F02)~~
【分類號(hào)】：TP391.41
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本文編號(hào)：1606540