Affiliations: [a]
ECE Department, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari District, Tamilnadu, India
| [b]
ECE Department, St. Xavier’s Catholic College of Engineering, Chunkankadai, Kanyakumari District, Tamilnadu, India
| [c]
BME Department, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari District, Tamilnadu, India
Correspondence:
[*]
Corresponding author. S. Amala Shanthi, Associate Professor, ECE Department, Noorul Islam Centre for Higher
Education, Kumaracoil, Kanyakumari District, Tamilnadu 629180, India. Tel.: +91 7598446730; E-mail:
amalashanthi69@gmail.com.
Abstract: A vital task in image denoising is to preserve edges and image features while removing noise. This paper presents an efficient algorithm for noise removal by incorporating an adaptive bilateral filter in the subsampled pyramid and nonsubsampled directional filter bank (SPNSDFB). This filter bank decomposes the noisy image into subbands of different frequency and orientation. Owing to its multiscale, multidirectional and lack of shift variance capability, it provides an efficient representation of intrinsic geometric structures of an image. By the fusion of the bilateral filter in SPNSDFB domain and optimum selection of parameters of the adaptive bilateral filter, the proposed algorithm minimizes mean square error (MSE) between the original image and the denoised image even at high noise densities. Experimental results show that the algorithm is found to be competitive in denoising performance due to its better edge preservation and improves peak signal-to-noise-ratio and image visual impression.
Keywords: Directional filter bank (DFB), subsampled pyramid (SP), nonsubsampled directional filter bank (NSDFB), fan filter
