A new image denoising algorithm to deal with the Poisson noise model is given, which is based on the idea of Non-Local Mean. By using the ”Oracle” concept, we establish a theorem to show that the Non-Local Means Filter can effectively deal with Poisson noise with some modification. Under the theoretical result, we construct our new algorithm called Non-Local Means Poisson Filter and demonstrate...

Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age. All digital images contain some degree of noise. Removing noise from the original signal is still a challenging problem for researchers. In this paper, the non-local denoising approach presented by Buades et al. is compared and analyzed by Fast nonlocal means algorithm. Th...

Due to the limitation of the local spatial information in an image, fuzzy c-means clustering algorithms with the local spatial information cannot obtain the satisfying segmentation performance on the image heavily contaminated by noise. In order to compensate this drawback of the local spatial information, an effective kind of non-local spatial information is extracted from the image in this pa...

<span>One of the main difficulties facing certified documents documentary archiving system is checking stamps system, but, that may be contains complex background and surrounded by unwanted data. Therefore, objective this paper to isolate remove noise stamp. Our proposed method comprises four phases, firstly, we apply k-means algorithm for clustering stamp image into a number clusters mer...

Noise filtering is a common step in image processing, and is particularly effective in improving the subjective quality of images. A large number of techniques have been developed, many of which concentrate on the problem of removing noise without damaging small structures such as edges. One recent approach that demonstrates empirical merit is the non-local means (NLM) algorithm. However, in or...

In this letter, we investigate the shrinkage problem for the non-local means (NLM) image denoising. In particular, we derive the closed-form of the optimal blockwise shrinkage for NLM that minimizes the Stein’s unbiased risk estimator (SURE). We also propose a constant complexity algorithm allowing fast blockwise shrinkage. Simulation results show that the proposed blockwise shrinkage method im...