Paper Contents
Abstract
Image de-noising is the pre-processing task which is most important step in image processing. It reduces the impact of the noise signals in the images. Noise signals are unwanted signals which deteriorate the quality of images and suppress the important details in the images. Image processing is one of the important research area in various fields viz. remote sensing, law enforcement, surveillance, astronomy, medical science etc. In the area of medical field; various types of imaging techniques are to be used. Some of the most common techniques are X-ray imagining, computed tomography imaging, ultrasound imaging, magnetic resonance imagining, positron emission tomography imaging etc. These imaging techniques are severely affected by different types of noises; e. g. computed tomography images, ultrasound images and magnetic resonance images are affected by additive white Gaussian noise, speckle noise and rician noise respectively. Manu researchers have developed various techniques to reduces the impact of the noise signals from medical images however no any technique is so efficient enough to reduce the all types of noise signals from all types of images because all the noise signals have different characteristics. Gaussian noise is additive in nature while speckle noise is multiplicative. There are still room to develop more efficient de-noising techniques which have better efficacy than the existing techniques. The man objective of our research is to suppress speckle noise signals from ultrasound images hence to understand the characteristics of speckle noise and existing techniques various research papers have been studied and findings and limitations to be found so that a novel technique can be developed which may give better performance.
Copyright
Copyright © 2025 Anjali, Shajid Ansari, Parineeta Jha. This is an open access article distributed under the Creative Commons Attribution License.
