基于矢量量化的模糊參數(shù)辨識(shí)及分辨率增強(qiáng)方法
A VQ-Based Parameter Identification Approach to Blind Image Restoration and Resolution Enhancement
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摘要: 在實(shí)際的圖像復(fù)原中通常需要預(yù)先估計(jì)模糊函數(shù)。該文將Nakagaki等人提出的基于矢量量化的模糊參數(shù)辨識(shí)算法進(jìn)行改進(jìn)，利用Sobel 算子形成特征矢量，避免了LOG濾波器參數(shù)的選擇，增強(qiáng)了算法對(duì)辨識(shí)不同類(lèi)型圖像的模糊函數(shù)的魯棒性，并利用DCT對(duì)特征矢量降維，減小了計(jì)算量。同時(shí)將其應(yīng)用于超分辨率圖像復(fù)原中，辨識(shí)出多幅低分辨率圖像的模糊函數(shù)，然后融合具有不同模糊函數(shù)和信噪比的低分辨率圖像，實(shí)現(xiàn)了盲超分辨率圖像復(fù)原。仿真結(jié)果表明了改進(jìn)算法的有效性和可行性。
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關(guān)鍵詞:
- 圖像復(fù)原;盲超分辨率;參數(shù)辨識(shí);矢量量化;Sobel算子
Abstract: Blur identification is usually necessary in image recovery. In this paper, an improved approach is proposed on the basis of VQ-based blur identification algorithm developed by Nakagaki, In this method, Sobel operator is used for extracting feature vectors, so that the selection of the parameter of the LOG filter is avoided and this method is robust to different types of images. The dimensionality of the vector is reduced by utilizing DCT. Meantime, extension of this method to blind super-resolution image restoration is achieved. After blur identification, a super-resolution image is reconstructed from several low-resolution images obtained by different foci. Simulation results demonstrate the feasibility and validity of the method. -
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