Combined Wavelet Domain and Temporal Video Denoising
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Space-Time Adaptation for Patch-Based Image Sequence Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
Patch-based video processing: a variational Bayesian approach
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Image sequence denoising via sparse and redundant representations
IEEE Transactions on Image Processing
Generalizing the Nonlocal-means to super-resolution reconstruction
IEEE Transactions on Image Processing
Super resolutionwith probabilistic motion estimation
IEEE Transactions on Image Processing
Motion tuned spatio-temporal quality assessment of natural videos
IEEE Transactions on Image Processing
Video denoising algorithm in sliding 3D DCT domain
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Spatio-temporal adaptive 3-D Kalman filter for video
IEEE Transactions on Image Processing
On the origin of the bilateral filter and ways to improve it
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Optimal Spatial Adaptation for Patch-Based Image Denoising
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Wavelet-Domain Video Denoising Based on Reliability Measures
IEEE Transactions on Circuits and Systems for Video Technology
Video Denoising Based on Inter-frame Statistical Modeling of Wavelet Coefficients
IEEE Transactions on Circuits and Systems for Video Technology
An Improved Motion-Compensated 3-D LLMMSE Filter With Spatio–Temporal Adaptive Filtering Support
IEEE Transactions on Circuits and Systems for Video Technology
SURE-LET for Orthonormal Wavelet-Domain Video Denoising
IEEE Transactions on Circuits and Systems for Video Technology
Video Denoising Based on a Spatiotemporal Gaussian Scale Mixture Model
IEEE Transactions on Circuits and Systems for Video Technology
Adaptive motion-compensated filtering of noisy image sequences
IEEE Transactions on Circuits and Systems for Video Technology
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A video denoising algorithm, which is based on dynamic nonlocal means (DNLM), is developed. Firstly, the standard nonlocal means and Kalman filtering are reviewed briefly. Then, using the idea of nonlocal means and linear minimum variance fusion, a weighted translational motion model without the explicit motion estimation and a weighted translational observation model are proposed to modify the state transition and observation equations. Finally, the overall dynamic denoising algorithm under the Kalman filter framework is presented. The main contribution of our work is a dynamic nonlocal means algorithm that is developed for video denoising under the Kalman filtering framework. In this algorithm, all computations are pixel-wise and it is easy to realize an efficient recursive algorithm for real-time processing. Experimental results for different test videos demonstrate the power of proposed method based on peak signal-to-noise-ratio (PSNR), structural similarity (SSIM) and motion-based video integrity evaluation index (MOVIE). The proposed method performs better than SNLM with the average PSNR gain of 2.33dB, and outperforms SEQWT, 3DWTF and IFSM with the average SSIM gains of 0.033, 0.0087 and 0.049. It has competitive performance with STA, WRSTF and 3DSWDCT, but needs lower computational cost. Though the proposed DNLM is not competitive with several state-of-the-art video denoising algorithms such as VBM3D, K-SVD, 3D-Patch, and ST-GSM, it may be anyway valuable to readers working in this field as a source of inspiration for their further researches.