Multi-core Median Redescending M-Estimator for Impulsive Denoising in Color Images

Mújica-Vargas, Dante; Rendón-Castro, Arturo; Matuz-Cruz, Manuel; García-Aquino, Christian

doi:10.1007/978-3-030-77004-4_25

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [ 32 ], a median redescending estimator was employed for impulsive denoising in grayscale images. Furthermore, in [ 33 ], we extended the median redescending M-estimator for color images, multi-core processing, and random-value impulsive noise. These robust estimations utilize redescending influence functions (

) for effective impulsive noise elimination.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Image Quality via Robust Noise Filtering Using Redescending M-Estimators

Rendón-Castro

Mújica-Vargas

Luna-Álvarez

et al. 2023

Entropy

Self Cite

View full text Add to dashboard Cite

In the field of image processing, noise represents an unwanted component that can occur during signal acquisition, transmission, and storage. In this paper, we introduce an efficient method that incorporates redescending M-estimators within the framework of Wiener estimation. The proposed approach effectively suppresses impulsive, additive, and multiplicative noise across varied densities. Our proposed filter operates on both grayscale and color images; it uses local information obtained from the Wiener filter and robust outlier rejection based on Insha and Hampel’s tripartite redescending influence functions. The effectiveness of the proposed method is verified through qualitative and quantitative results, using metrics such as PSNR, MAE, and SSIM.

show abstract

) for effective impulsive noise elimination.…”

Section: Related Workmentioning

confidence: 99%