Open Access Open Access  Restricted Access Subscription or Fee Access

An Edge-preserving Adaptive Image Denoising using Discrete Wavelet Transform

Ram Paul, Singara Singh Kasana, Rajesh Kumar Gupta


Captured images got corrupted due to noise in additive or multiplicative form. It is necessary to reduce these noises for further image processing while preserving the edges present in the image. In this work, an edge-preserving adaptive scheme for image denoising is proposed. The noisy image is decomposed using discrete wavelet transform. Then two thresholds are calculated by using the Bayesian estimator. These thresholds are used to denoise the transformed image using soft thresholding. The first adaptive threshold is used for flatten region and second threshold is used for edges region as the noise has low visual perception on the edges. Experimental results show that this scheme achieves the state-of-the-art performance for image denoising. The results of these adaptive schemes are compared by Peak Signal-to-Noise Ratio (PSNR) and visual perception with existing denoising techniques.


Image denoising, Bilateral filtering, BM3D filtering, Edge-preserving adaptive thresholding and PSNR.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.