چکیده (انگلیسی):

Now-a-days the images acquired by the digital cameras and
defective sensors tend to introduce noises during either image
acquisition or transmission process. The quality of the image is
degraded in a significant measure. Lot of research works was carried
out for several decades to denoise the impulse noise and each approach
has its own merits and demerits. This study deals with a new
denoising approach for the gray scale images to discard fixed type salt
and pepper noise present in the images. This algorithm was
implemented for gray scale images such as Lena and cameraman and
the performance results are really challenging both qualitative and
quantitative wise. This study considered the performance metrics like
PSNR and MSE for quantitative measure and presents better results
for low density noise level to high density noise level (up to 100%),
when compared to other existing filters. The visual interpretation
shows that this method proves better in qualitative analysis by human
perception too. In addition to this the proposed approach decreases the
computational and hardware complexity by an appreciable manner
since traditional sorting schemes does many comparisons and that
were very much avoided. Thus very fast operation could be achieved.
This study deals with neighborhood pixel comparison which are
confined to previous pixel and the pixel next to the processing pixel
under consideration, the absence of sorting saves much time and
number of operations, which in turn speed of operation is increased
and better reconstruction of images is achieved.