A Modified Structure of Local Adaptive Hysteresis Smoothing for Image Denoising
Ali Sabet Nasab, Reza P.R. Hasanzadeh, Pooriya Takhtechian
⚠ This is a preprint. It may change before it is accepted for publication.

Abstract

Conventionally, Hysteresis Smoothing (HS)-based techniques rely on hysteresis thresholds to eliminate noise. The most efficient of the HS techniques, namely LAHS, performs well in image denoising; however, its structure has limitations in removing noise while preserving details. In this paper, a new framework, called Modified LAHS (MLAHS), is proposed to overcome these problems by modifying the cursor-width strategy and the HS process. The proposed method is evaluated quantitatively and qualitatively against other noise-reduction methods. The results show that the proposed structure significantly improves the performance of LAHS and also outperforms several efficient and widely used noise-suppression techniques.

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