Sparse Bilateral Denoising for CT Scan Images with Edge Preservation
Veni N1, Manjula J2, Vivek Maik3
1Veni N, Department of ECE, SRMIST, Chennai (Tamil Nadu), India.
2Mnjula J, Department of ECE, SRMIST, Chennai (Tamil Nadu), India.
3Vivek Maik, Department of ECE, SRMIST, Chennai (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 384-387 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10810886S19/19©BEIESP | DOI: 10.35940/ijeat.F1081.0886S19
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Abstract: Denoising in CT images using bilateral with sparse representation is presented in this paper. Artifacts occurs in images when an X-ray penetrates the thick objects like bones, implanted organs, surgical clips etc.,. Due to these artifacts in images , the quality of artifact pruning algorithms will be diminished. In order to preserve the image quality as well as edge details, a bilateral filter along with sparse representation is proposed to reduce the noises. The proposed technique is applied to CT humorous bone image and has achieved the better PSNR of 22dB approximately for 512 x512 image as compared to bicubic filter. The simulated real datasets are used to quantitatively evaluate the noise. Moreover the proposed denoising approach can outperform the latest approach in terms of fidelity
Keywords: CT Image, Denoising, Bilateral Filter, Sparse Representation, Dictionary Learning.
Scope of the Article: Image Security