Author:
Sarode M. V.,Deshmukh P. R.
Abstract
In this paper, we investigate the denoising of image sequences i.e. video, corrupted with Gaussian noise and Impulse noise. In relation to single image denoising techniques, denoising of sequences aims to utilize the temporal dimension. This approach gives faster algorithms and better output quality. This paper focuses on the removal of different types of noise introduced in image sequences while transferring through network systems and video acquisition. The approach introduced consists of motion estimation, motion compensation, and filtering of image sequences. Most of the estimation approaches proposed deal mainly with monochrome video. The most usual way to apply them in color image sequences is to process each color channel separately. In this paper, we also propose a simple, accompanying method to extract the moving objects. Our experimental results on synthetic and natural images verify our arguments. The proposed algorithm’s performance is experimentally compared with a previous method, demonstrating comparable results.
Publisher
Engineering, Technology & Applied Science Research
Reference17 articles.
1. M. Protter, M. Elad, “Image Sequence Denoising via Sparse and Redundant Representations”, IEEE Transactions on Image Processing, Vol. 18, No. 1, pp. 27-35, 2009
2. D. S. Alexiadis, G. D. Sergiadis, “Estimation of Motions in Color Image Sequences Using Hypercomplex Fourier Transforms”, IEEE Transactions on Image Processing, Vol. 18, No. 1, pp. 168-187, 2009
3. M. Elad, M. Aharon, “Image Denoising via Learned Dictionaries and Sparse Representation”, International Conference Computer Vision and Pattern Recognition, New York, 2006
4. M. Elad, M. Aharon, “Image Denoising via Sparse and Redundant Representation Over Learned Dictionaries”, IEEE Transactions on Image Processing, Vol. 15, No. 12, pp. 3736–3745, 2006
5. A. Buades, B. Coll, J. M. Morel, “A Review of Image Denoising Algorithms, with a New One”, Multiscale Modeling & Simulation, Vol. 4, No. 2, pp. 490–530, 2005
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献