基于能量函數(shù)的極值中值濾波星圖去噪算法
doi: 10.11999/JEIT160955
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2.
(中國科學(xué)院長春光學(xué)精密機(jī)械與物理研究所 長春 130033) ②(中國科學(xué)院大學(xué) 北京 100049)
基金項(xiàng)目:
國家863計(jì)劃項(xiàng)目(2011AA8082035)，中國科學(xué)院長春光學(xué)精密機(jī)械與物理研究所三期創(chuàng)新工程資助項(xiàng)目(065X32CN60)
Extremum Median Filter Map Denoising Algorithm Based on Energy Function
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2.
(Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)
Funds:
The National 863 Program of China (2011AA 8082035), The Third Phase of Innovative Engineering Projects of the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (065X32CN60)
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摘要: 利用地基觀測相機(jī)拍攝的以深空為背景的星圖受星空復(fù)雜背景的影響，往往具有較高的噪聲水平。同時由于星圖主要由恒星、空間目標(biāo)和星空背景噪聲組成，且成點(diǎn)狀分布，星圖目標(biāo)和噪聲呈現(xiàn)較大的相似性，傳統(tǒng)的圖像去噪算法并不適用于星圖。為此，該文提出一種基于能量函數(shù)的極值中值濾波去噪算法，該算法在去除星圖椒鹽噪聲的同時能夠較好地保持圖像目標(biāo)信息。該方法針對疑似噪聲點(diǎn)采用二次檢測的方式，并且結(jié)合改進(jìn)的自適應(yīng)中值濾波和能量函數(shù)模型進(jìn)行灰度值恢復(fù)。該文分別使用仿真試驗(yàn)和真實(shí)星圖處理試驗(yàn)對該方法進(jìn)行驗(yàn)證，在客觀評價中，圖像峰值信噪比PSNR(Peak Signal to Noise Ratio)最高可提高3倍多，均方誤差MSE(Mean Squared Error)減小為加噪圖像的 。試驗(yàn)結(jié)果表明，該方法可有效地降低傳統(tǒng)方法的噪聲誤檢問題，同時提高噪聲圖像的恢復(fù)精度，非常適合星圖噪聲的去除。Abstract: The star maps acquired by the ground-based cameras are susceptible to the complex background of the starry sky and thus have high noise levels. In addition, the targets in star maps are similar to the noises due to their punctate shapes. As a result, the traditional image denoising method is not applicable to star maps. A new adaptive extremum median filtering denoising algorithm is put forward based on energy function, which can effectively remove the salt and pepper noise of the star maps and keep the small target information at the same time. This method employs a twice-check strategy to reduce the false detection ratio of noisy pixels and uses the improved adaptive median filter and the energy function model to recovery noise imagery. The simulated and real star map experiments show that, the Peak Signal to Noise Ratio (PSNR) is improved about 3 times and the Mean Squared Error (MSE) is reduced by in the terms of objective evaluations, the proposed method can effectively improve the denoising result and thus is applicable to star maps.
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