Impulse Noise Removal Using Soft-computing

  • Hafiz Muhammad Tayyab Khushi Department of Software Engineering, Superior University Lahore
Keywords: Image fusion, Multi focus image fusion, Blurring, blurred images, spatial, Convolutional Neural Network, Activity level measurements


Image restoration has become a powerful domain now a days. In numerous real life applications Image restoration is important field because where image quality matters it existed like astronomical imaging, defense application, medical imaging and security systems. In real life applications normally image quality disturbed due to image acquisition problems like satellite system images cannot get statically as source and object both moving so noise occurring. Image restoration process involves to deal with that corrupted image. Degradation model used to train filtering techniques for both detection and removal of noise phase. This degeneration is usually the result of excess scar or noise. Standard impulse noise injection techniques are used for standard images. Early noise removal techniques perform better for simple kind of noise but have some deficiencies somewhere in sense of detection or removal process, so our focus is on soft computing techniques non classic algorithmic approach and using (ANN) artificial neural networks. These Fuzzy rules-based techniques performs better than traditional filtering techniques in sense of edge preservation.

How to Cite
Hafiz Muhammad Tayyab Khushi. (2022). Impulse Noise Removal Using Soft-computing. Lahore Garrison University Research Journal of Computer Science and Information Technology, 6(1), 32-48.