Graduate from Indian Institute of Science Education & Research (IISER), Kolkata

AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

Public Audience

English

120 Minutes

Saarbrücken

There are numerous contemporaneous techniques in the field of Impulse noise mitigation and hence the bar for deciding the efficiency of pristine algorithms is quite high. The prime motive of the talk is to introduce the mechanisms, our research group has proposed, for Salt-and-Pepper (SAP) and Random Valued (RV) Impulse Noise elimination from images. In the case of SAP noise mitigation, the novelty lies in the manner in which the size of the kernel was manipulated depending upon the noise percentage in the image. Eventually, the required number of noise free pixels were obtained for subsequent Cardinal Spline Interpolation to eliminate the noisy center pixel of the kernel. The detection of RV Noise is quite demanding when compared to its counterpart. The basic concept that the “variation among the pixels in a neighborhood is minimum”, was made use of to the fullest extent, to propose a mathematical algorithm and subsequently detect RV noise. Once the detection was complete, Cardinal Spline interpolation framework was used to interpolate the noise free pixels to replace the noisy pixel. The obtained restored images were superior when compared to the results of other existing algorithms in terms of statistical yardsticks like Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). Furthermore, the RV noise elimination technique was also extended to 3D mesh networks for noise mitigation.

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