Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2010-02-05
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/A-C
Computer Science
Computer Vision and Pattern Recognition
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/A-C
Scientific paper
This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN). Different noise densities have been removed between 10% to 60% by using five types of filters as Mean Filter (MF), Adaptive Wiener Filter (AWF), Gaussian Filter (GF), Standard Median Filter (SMF) and Adaptive Median Filter (AMF). The same is applied to the Saturn remote sensing image and they are compared with one another. The comparative study is conducted with the help of Mean Square Errors (MSE) and Peak-Signal to Noise Ratio (PSNR). So as to choose the base method for removal of noise from remote sensing image.
Al-amri Salem Saleh
Kalyankar Namdeo V.
Khamitkar Santosh D.
No associations
LandOfFree
A Comparative Study of Removal Noise from Remote Sensing Image does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Comparative Study of Removal Noise from Remote Sensing Image, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Comparative Study of Removal Noise from Remote Sensing Image will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-535122