(1. 中南大學(xué) 信息科學(xué)與工程學(xué)院，長(zhǎng)沙 410083；
2. 湖南文理學(xué)院 電氣與信息工程學(xué)院，常德 415000)
摘 要: 針對(duì)礦物浮選過程中泡沫圖像易受噪聲影響，存在紋理細(xì)節(jié)模糊、灰度值對(duì)比度低等問題，提出一種浮選泡沫圖像的非線性降噪方法。首先構(gòu)造一種改進(jìn)方向波變換，保證信號(hào)的平移不變性，同時(shí)采用提升算法減小其運(yùn)算量。然后通過對(duì)分解系數(shù)建模，針對(duì)低頻子帶系數(shù)采用多尺度Retinex算法進(jìn)行處理，以改善整體亮度均勻性，提高對(duì)比度；對(duì)各高通子帶構(gòu)建基于高斯混合尺度模型的分解系數(shù)鄰域模型，并利用Bayes最小均方(BLS)估計(jì)進(jìn)行局部去噪。最后利用所提出的方法對(duì)大量浮選泡沫圖像進(jìn)行去噪分析。結(jié)果表明：所提出的降噪方法能突出泡沫圖像的紋理細(xì)節(jié)信息，提高泡沫圖像的對(duì)比度，在信噪比和實(shí)時(shí)性上有明顯提高，為后續(xù)泡沫圖像的分割和工況識(shí)別奠定基礎(chǔ)。
關(guān)鍵字: 浮選泡沫圖像；圖像降噪；方向波變換；高斯混合尺度模型；Retinex算法
（1. School of Information Science and Engineering, Central South University, Changsha 410083, China;
2. College of Electrical and Information Engineering, Hunan University of Arts and Science, Changde 415000, China）
Abstract:Considering the defects, such as easy sensitivity to noise and heavy texture, low contrast of gray value in the process of the floatation of foam image, a non-linear de-noising method was proposed. Lifting improved directionlet transform was firstly constructed, which not only ensured the shifting invariance but reduced its complexity. Multi-scale Retinex algorithm dealing with low-frequency subband coefficient was proposed for improving luminance uniformity and overall contrast. For high-pass subband, a model of decomposition coefficients neighbourhood based on Gaussian scale mixtures model was proposed for de-noising the image locally using Bayes least square (BLS). The analysis on the effect of de-noising was given to lots of real froth images. The results show that the proposed method is successful in maintaining edges and is superior in de-noising in term of PSNR and visual effect. It lays a foundation for foamy segmentation and analyzing grade from flotation froth image.
Key words: flotation froth image; image de-noising; directionlet transform (DT); Gaussian scale mixture (GSM); Retinex algorithm
