A novel algorithm for detection and removal of random valued impulse noise using cardinal splines

Self Cite

In this research effort, we propose a novel mesh smoothing algorithm using Cubic B-Splines. The basic fact that the coordinates of neighboring vertices of a mesh vary insignificantly is the underlying idea of this paper. The mesh reconstruction is performed by replacing the corrupt vertices which are responsible for the rugged topology of the mesh by interpolating the original noise-free vertices. The final reconstructed meshes were quantitatively measured using Signal to Noise ratio. The results were impressive both in quantitative and visual terms.

Section: Resultsmentioning

confidence: 99%

“…Spline interpolation has been extensively used in reconstruction techniques [4,5,8]. The meshes with the rugged topology in this paper were generated by using the denoising algorithm proposed by Bodduna et al in [6].…”

mentioning

confidence: 99%

A Fast and Efficient Mesh Smoothing Algorithm for 3D Graphical Models Using Cubic B-Splines

Roy

Bodduna

Kumari

et al. 2015

Self Cite

“…B-Splines are used for interpolation because they have compact support passes through control point and have local propagation property. The idea of interpolation has been taken from Kireeti Bodduna and Rajesh Siddavatam [10] where they have applied the below methodology to solve the problem of random valued Impulse Noise removal using Cardinal Spline Interpolation [10].…”

Section: Proposed B-spline Interpolation Algorithmmentioning

confidence: 99%

A Novel Algorithm for Suppression of Salt and Pepper Impulse Noise in Fingerprint Images Using B-Spline Interpolation

Sree

Pattnaik

Ghrera

2015

Abstract. The quality of Finger Print Images in image forensics plays a vital role in the the accuracy of biometric based identification and authentication system. To suppress the salt and pepper noise in fingerprint images, B-Splines have been used for interpolation. In this paper, a two stage novel and efficient algorithm for suppression of salt and pepper impulse noise for noise levels ranging from 15 % to 95 % using B-splines interpolation is being proposed. The algorithm removes salt and pepper impulse noise from the image in the first stage and in second stage, an edge preserving algorithm has been proposed which regularizes the edges that have been deformed during noise removal process.

“…It can be broadly classified into two categories i.e. salt and pepper noise because the noisy pixel candidate can take value either 0 (darkest) or 255 (brightest) and random valued impulse noise in which noisy pixel candidate can take value varying in the range of 0-255 [6], making it hard to detect because in local neighborhood difference between noisy and noise free pixels are not significant and also, its existence cannot be determined by image histogram [7]- [8].…”

Section: Introductionmentioning

confidence: 99%

An Expeditious Algorithm for Random Valued Impulse Noise Removal in Fingerprint Images Using Basis Splines

Saxena

2015

Abstract. In image forensics, the accuracy of biometric based identification and authentication system depends upon the quality of fingerprint images. The quality of the fingerprint images gets compromised by the introduction of various kinds of noise into them. The fingerprint images may get corrupted by random valued impulse noise mainly during the capturing or transmission process. To obtain noise free fingerprint images, they are processed using noise removal methods and filters. In this paper, a two stage novel and efficient algorithm for suppression of random valued impulse noise using basis splines interpolation is proposed. The algorithm removes noise from the image in the first stage and in second stage, it regularizes the edge deformed during noise removal process.