Image De-Noising with Wavelet Transform and Biorthogonal Technique

Authors: Manvendra S. Lodhi, Rahul Kaul

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Abstract

Image denoising technique has a common approach in the image transmission and many methods used for information retrieval from images uses the image denoising. The thresholding approach has been applied on wavelet coefficient for de-noising of images. Many research papers have been published for the way of applying threshold on the wavelet coefficients. In this paper, modified approach for soft threshold has been used. Two thresholds have been applied for modifying the wavelet coefficient. Different wavelet transform family has been applied for image de-nosing process. The performance of the proposed method was given in tem of PSNR and MSE.

Introduction

he image is an important data type, which helps to find the information in quick manner. The noise free image to user is prime concern of various service providers. The images are corrupted by various type of noises like Gaussian noise, salt and pepper noise, passion noise etc., It is a mandatory requirement to remove the noise before use the image for any information retrieval system. Different methods of image denoising are in use for image denoising. The figure 1 shows the classification of image denoising methods.

Conclusion

The proposed method is successfully applied for image de-noising and giving better result compare to other methods as shown in table1. For low SNR, proposed biorthogonal method showing better results. ~ 20 % mean square error has been reduces with the proposed method at noise sigma is more than 20. Which effect increase the PSNR by ~ 2dB