Impulse Noise Removal Using Soft-computing
Hafiz Muhammad Tayyab Khushi, Suleman Asjed, Tehreem Masood, Arfan Jaffar · Lahore Garrison University Research Journal of Computer Science and Information Technology · 2022
Image restoration has become a powerful domain nowadays. Image restoration is essential in numerous real-life applications because where image quality matters, it exists, like astronomical imaging, defence application, medical imaging, and security systems. In real-life applications, image quality is generally disturbed due to image acquisition problems like satellite system images cannot get statically as the source and object are both moving, so noise occurs. This degeneration is usually the result of excess scar or noise. The image restoration process involves dealing with that corrupted image, the degradation model trains filtering techniques for detecting and removing the noise phase. Standard impulse noise injection techniques are used for traditional images. Early noise removal techniques perform better for simple noise but have deficiencies in the detection or removal process. Hence, our focus is on soft computing techniques, non-classic algorithmic approaches and using (ANN) artificial neural networks. These Fuzzy rules-based techniques perform better than traditional filtering techniques in edge preservation.