A combined approach for noise reduction in medical images using Dual Tree Discrete Wavelet Transform and Rotated Dual Tree Discrete Wavelet Transform

Abstract

Medical imaging suffers from image noise. To remove this noise spatial domain and transform domain techniques are used. But spatial domain techniques have limitation of edge blurring w.r.t transform based techniques .Therefore in this paper we have proposed a transform based denoising technique. We have used Dual tree DWT and Rotated version of Dual Tree DWT jointly to improve our denoising results. Our main focus is to get more directional information from this transform which will improve denoising results. We have compared our results with existing methods and results are very encouraging. PSNR is used as image quality measure.

Noise Cancellation in Computed Tomography Images through Adaptive Multi-Stage Noise Removal Paradigm

“…To prove the effectiveness of the proposed methodology, we compare our algorithm with different methods as shown in Table II. In this performance analyze, we compare our proposed method with already published literatures like Dual Tree Complex Wavelet (DTCWT) [22], Curvelet Transform (CT) [22], Harris and DWT [23], Harris Operator and Wavelet Domain Thresholding (RDTDWT) [24], SRTW [25]. When analyzing the above table our proposed method achieves a higher accuracy and higher PSNR of 42.05 because in our work multilevel denoising is performed as well as adaptive bilateral filter is used.…”