Image denoising based on wavelet transformVol.32, No.1 Jan, 2005Opto-Electronic EngineeringVol.32, No.1 Jan, 2005Article number: 1003-501X (2005) 01-0051-04Image denoising based on wavelet transformRui Ting1, 2, Wang Jinyan3, Shen Chunlin1, Ding Jian2( 1. School of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China; 2. Engineering College of PLA University of Science and Technology, Nanjing 210007, Jiangsu, China; 3. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China )Abstract: A new denoising method based on estimating the noise energy in the wavelet domain is proposed. The algorithm uses discrete cosine transform (DCT) to extract the main features of wavelet coefficients without estimating the noise variance. The image is decomposed by wavelet, and local features of high-frequency subbands are extracted using DCT; wavelet coefficients are reconstructed using part of DCT coefficients, and the average energy of the reconstructed coefficients is used as the estimation of local noise energy; after removing the noise components in the original wavelet coefficients, an inverse wavelet transform is performed to obtain the denoised image. Experiments have shown that its peak signal-to-noise ratio (PSNR) is 2-4 dB higher than that of the usual threshold shrinkage method. Keywords: image processing; wavelet transform; discrete cosine transform; denoisingCLC number: TN911.7 Document code: AWavelet image denoising based on discrete cosine transformRUI Ting1, 2, WANG Jin-yan3, SHEN Chun-lin1, DING Jian2 (1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 2. Engineering Institute of Engineering C……
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