An Efficient Approach for Denoising of CT-Images Using EMD and Dual Tree Complex Wavelet Packets

Abstract

Computed tomography (CT) images are generally corrupted by several noises from the measurement process complicating the automatic feature extraction and analysis of clinical data. To achieve the best possible diagnosis it is important that medical images be sharp, clear, and free of noise and artifacts. While the technologies for acquiring digital medical images continue to improve, resulting in images of higher and higher resolution and quality, noise remains an issue for many medical images. Removing noise in these digital images remains one of the major challenges in the study of medical imaging. A variety of literatures have been developed to solve the problem of medical images denoising which is a significant stage in an automatic diagnosis system. In this paper, we propose a new image denoising technique using EMD and Dual Tree Complex Wavelet Packets. Here, histon process is used in order to overcome the smoothing filter type and it will not affect the lower dimensions. We have used two noises, like as Gaussian and salt & pepper for the proposed technique. The performance of the proposed image denoising technique is evaluated on the five CT images using the PSNR and SDME. For comparison analysis, our proposed denoising technique is compared with the existing work in various noise levels. From the results, we can conclude that the proposed denoising technique has shown the SDME of 48.33 but the existing technique show the PSNR of 39.84 for salt & pepper noise.