EBMBDT : Effective Block Matching Based Denoising Technique using Dual Tree Complex Wavelet Transform

• Autorzy: Selvi M.

Identyfikatory

DOI

10.22630/MGV.2014.23.3.3

• Języki publikacji: EN

Abstrakty

EN

In processing and investigation of digital image denoising of images is hence very important. In this paper, we propose a Hybrid denoising technique by using Dual Tree Complex Wavelet Transform (DTCWT) and Block Matching Algorithm (BMA). DTCWT and BMA is a method to identify the noisy pixel information and remove the noise in the image. The noisy image is given as input at first. Then, bring together the comparable image blocks into the load. Afterwards Complex Wavelet Transform (CWT) is applied to each block in the group. The analytic filters are made use of by CWT, i.e. their real and imaginary parts from the Hilbert Transform (HT) pair, defending magnitude-phase representation, shift invariance, and no aliasing. After that, adaptive thresholding is applied to enhance the image in which the denoising result is visually far superior. The proposed method has been compared with our previous denoising technique with Gaussian and salt-pepper noise. From the results, we can conclude that the proposed de-noising technique have shown better values in the performance analysis.

Słowa kluczowe

EN

image denoising; complex wavelet transform; CWT; dual tree CWT; block matching; soft thresholding

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2014
• Tom: Vol. 23, No. 3/4
• Strony: 23--41
• Opis fizyczny: Bibliogr. 27 poz., il., wykr.

Twórcy

autor

Selvi M.

• Aloy Labs, I-901, Springfields Apts, Sarjapur Road, Bellandur Gate, Bangalore - 560102, India

Bibliografia

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