Gao, Tao; He, Xiuli Wavelet frame based denoising algorithm for color image with Poisson noise. (Chinese. English summary) Zbl 1474.42122 J. Nanjing Univ. Inf. Sci. Technol., Nat. Sci. 12, No. 5, 614-618 (2020). Summary: As an important factor influencing image quality, noise can blur characteristic details and reduce the signal to noise ratio, thus make the denoising critical in image processing. A wavelet frame based Poisson denoising model for color images is proposed in this paper, where the weighted \({\ell^2}\) is chosen as fidelity term and the \({\ell^1}\) item containing wavelet frame as a regularization item, while the reweighted split Bregman algorithm is employed to solve this model. Numerical experiments are carried out and PSNR indicators are used to assess the denoising effect of the proposed model. Results show that the algorithm is feasible and effective. Cited in 1 Document MSC: 42C15 General harmonic expansions, frames 94A08 Image processing (compression, reconstruction, etc.) in information and communication theory Keywords:wavelet frame; split Bregman algorithm; color image; Poisson noise PDFBibTeX XMLCite \textit{T. Gao} and \textit{X. He}, J. Nanjing Univ. Inf. Sci. Technol., Nat. Sci. 12, No. 5, 614--618 (2020; Zbl 1474.42122) Full Text: DOI