LOW COMPLEXITY EDGE DETECTION AND IMPULSE NOISE REMOVAL IN VARIOUS IMAGES

  • Pradeep.S et al.

Abstract

In this project the trilateral Subjective Sparse Coding [SSC] is proposed as a powerful image de-noising method. The intimation of our project is to remove noise and preserve edges of the image by using edge preservation technique. Our project is about de-noising in image processing. When the image is given as an input and the size of the image modifies to 512 x 512. After the input is given, the image is preprocessed by using preprocessing system. This preprocessing system is to determine the occurrence of the impulse noise in the input image. If the impulse noise appeared in the image then Edge preservation filter is used to preserve the edge and remove the impulse noise in images. Here there is a comparison between two types of filter which includes median filter and edge preservation filter. When an input is applied to a particular image there is a huge transformation from color image to the gray scale image. The input image attached is related to medical field and the general image. Further, patch by patch process was included to remove noise in the images. It shows that the proposed system is superior over the state of art filter for determining the parameters and getting a quality image.

Published
2019-12-31