Impulsive noise removal from color images with morphological filtering
Alexey Ruchay, Vitaly Kober

TL;DR
This paper introduces a new morphological filtering method for effectively removing impulse noise from color images, improving image quality and processing speed compared to existing algorithms.
Contribution
The paper presents a novel morphological filtering approach specifically designed for impulse noise removal in color images, demonstrating superior performance.
Findings
Effective impulse noise removal demonstrated through simulations
Outperforms existing algorithms in restoration quality
Faster processing speed than comparable methods
Abstract
This paper deals with impulse noise removal from color images. The proposed noise removal algorithm employs a novel approach with morphological filtering for color image denoising; that is, detection of corrupted pixels and removal of the detected noise by means of morphological filtering. With the help of computer simulation we show that the proposed algorithm can effectively remove impulse noise. The performance of the proposed algorithm is compared in terms of image restoration metrics and processing speed with that of common successful algorithms.
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Taxonomy
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
