• Anamika Jain
• Divyanshu Rao
• Prof. Ravimohan

In this work, investigation of several well-known algorithms for image denoising is carried out & their performance with their methodologies are comparatively assessed. A new algorithm based on the orthonormal wavelet transform (OWT) is developed. This shows better performance in comparison with the performance of other algorithms. In addition, it has been shown to enjoy the advantage of implementation simplicity. There are different types of noises that may corrupt an image in real life such as, salt-pepper noise, Sparkle noise shot noise, amplification noise, quantization noise etc. However, AWGN or Gaussian noise was considered in this work. A major part of the work was devoted to the review, implementation & performance assessment of published image denoising algorithms based on various techniques including the wavelet transform. The wavelet based approach finds applications in denoising images corrupted with Gaussian noise. The well-known Lena image corrupted with AWGN was denoised using OWT wavelet methods.

AWGN, Image Denoising, Noise, DWT, OWT

"Modified Gaussian Noise De-Noising using Orthonormal Wavelets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 4, page no.92-97, April-2017, Available :http://www.jetir.org/papers/JETIR1704023.pdf

"Modified Gaussian Noise De-Noising using Orthonormal Wavelets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 4, page no. pp92-97, April-2017, Available at : http://www.jetir.org/papers/JETIR1704023.pdf